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R/summarise_function.R
In AgroR: Experimental Statistics and Graphics for Agricultural Sciences
Defines functions
summarise_anova
Documented in
summarise_anova
#' Utils: Summary of Analysis of Variance and Test of Means
#'
#' @description Summarizes the output of the analysis of variance and the multiple comparisons test for completely randomized (DIC), randomized block (DBC) and Latin square (DQL) designs.
#' @author Gabriel Danilo Shimizu, \email{gabrield.shimizu@gmail.com}
#' @param analysis List with the analysis outputs of the DIC, DBC, DQL, FAT2DIC, FAT2DBC, PSUBDIC and PSUBDBC functions
#' @param design Type of experimental project (DIC, DBC, DQL, FAT2DIC, FAT2DBC, PSUBDIC or PSUBDBC)
#' @param round Number of decimal places
#' @param divisor Add divider between columns
#' @param inf Analysis of variance information (can be "p", "f", "QM" or "SQ")
#' @note Adding table divider can help to build tables in microsoft word. Copy console output, paste into MS Word, Insert, Table, Convert text to table, Separated text into:, Other: |.
#' @note The column names in the final output are imported from the ylab argument within each function.
#' @note This function is only for declared qualitative factors. In the case of a quantitative factor and the other qualitative in projects with two factors, this function will not work.
#' @note Triple factorials and split-split-plot do not work in this function.
#' @return returns a data.frame or print with a summary of the analysis of several experimental projects.
#' @import knitr
#' @export
#' @examples
#'
#'
#' library(AgroR)
#'
#' #=====================================
#' # DIC
#' #=====================================
#' data(pomegranate)
#' attach(pomegranate)
#' a=DIC(trat, WL, geom = "point", ylab = "WL")
#' b=DIC(trat, SS, geom = "point", ylab="SS")
#' c=DIC(trat, AT, geom = "point", ylab = "AT")
#' summarise_anova(analysis = list(a,b,c), divisor = TRUE)
#' library(knitr)
#' kable(summarise_anova(analysis = list(a,b,c), divisor = FALSE))
#'
#' #=====================================
#' vari=c("WL","SS","AT")
#' output=lapply(vari,function(x){
#' output=DIC(trat,response = unlist(pomegranate[,x]),ylab = parse(text=x),print.on=FALSE)})
#' summarise_anova(analysis = output, divisor = TRUE)
#'
#' #=====================================
#' # DBC
#' #=====================================
#' data(soybean)
#' attach(soybean)
#' a=DBC(cult,bloc,prod,ylab = "Yield")
#' summarise_anova(list(a),design = "DBC")
#'
#' #=====================================
#' # FAT2DIC
#' #=====================================
#' data(corn)
#' attach(corn)
#' a=FAT2DIC(A, B, Resp, quali=c(TRUE, TRUE))
#' summarise_anova(list(a),design="FAT2DIC")
summarise_anova=function(analysis,
inf="p",
design="DIC",
round=3,
divisor=FALSE){
requireNamespace("knitr")
if(design=="DIC"){
nlinhas=length(analysis[[1]]$dadosm$groups)
infor=data.frame(matrix(ncol=length(analysis),nrow = nlinhas))
trats=analysis[[1]]$dadosm$trats
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
letra=analysis[[i]]$dadosm$groups
transf=analysis[[i]]$transf
if(transf==1){media=round(analysis[[i]]$dadosm$resp,round)}
if(transf!=1){media=round(analysis[[i]]$dadosm$respO,round)}
infor[,i]=paste(media,letra)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
letra=analysis[[i]]$dadosm$groups
media=round(analysis[[i]]$dadosm$media,round)
infor[,i]=paste(media,letra)}
}
names(infor)=variable
rownames(infor)=trats
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
cvs[,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[2])/
mean(analysis[[i]]$resp)*100,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
cvs[,i]=" "}}
rownames(cvs)="CV(%)"
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
variable[i]=analysis[[i]]$plot$labels$y
if(tests=="parametric"){
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
if(tests=="noparametric"){
transf[,i]=""}
}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=1
infor1=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
pvalor=round(analysis[[i]]$anova[1,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
pvalor=round(analysis[[i]]$krusk$statistics[2],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}}
names(infor1)=variable
rownames(infor1)="p-value"
n=4
nc=1
infor2=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor2[,i]=round(analysis[[i]]$anova[1,n],round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor2[,i]=paste(round(analysis[[i]]$krusk$statistics[1][[1]],round),
"(Chisq)")}}
names(infor2)=variable
rownames(infor2)="F"
n=3
nc=2
infor3=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor3[,i]=""}
}
names(infor3)=variable
rownames(infor3)=c("QM_tr","QM_r")
n=2
nc=2
infor4=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor4[,i]=""}}
names(infor4)=variable
rownames(infor4)=c("SQ_tr","SQ_r")
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
norm[,i]=" "}}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
homog[,i]=" "}}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(infor,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(infor,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(infor,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(infor,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(infor,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="DBC"){
nlinhas=length(analysis[[1]]$dadosm$groups)
infor=data.frame(matrix(ncol=length(analysis),nrow = nlinhas))
trats=analysis[[1]]$dadosm$trats
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
letra=analysis[[i]]$dadosm$groups
transf=analysis[[i]]$transf
if(transf==1){media=round(analysis[[i]]$dadosm$resp,round)}
if(transf!=1){media=round(analysis[[i]]$dadosm$respO,round)}
infor[,i]=paste(media,letra)}
if(tests=="noparametric"){
letra=analysis[[i]]$dadosm$groups
media=round(analysis[[i]]$dadosm$media,round)
infor[,i]=paste(media,letra)}
}
names(infor)=variable
rownames(infor)=trats
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
cvs[,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[3])/
mean(analysis[[i]]$resp)*100,round)}
if(tests=="noparametric"){
cvs[,i]="-"}}
rownames(cvs)="CV(%)"
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
if(tests=="noparametric"){transf[,i]="-"}}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=2
infor1=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
pvalor=round(analysis[[i]]$anova[1:2,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
if(tests=="noparametric"){
pvalor=round(analysis[[i]]$fried$p.F,round)
infor1[,i]=c(ifelse(pvalor<0.001,"p<0.001",pvalor),
"-")}
}
names(infor1)=variable
rownames(infor1)=c("p_tr","p_bl")
n=4
nc=2
infor2=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
infor2[,i]=round(analysis[[i]]$anova[1:2,n],round)}
if(tests=="noparametric"){
infor2[,i]=c(round(analysis[[i]]$fried$`F`,round),
"-")}}
names(infor2)=variable
rownames(infor2)=c("F_tr","F_bl")
n=3
nc=3
infor3=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor3[,i]=c("-","-","-")}
}
names(infor3)=variable
rownames(infor3)=c("QM_tr","QM_bl","QM_r")
n=2
nc=3
infor4=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
if(tests=="noparametric"){
infor4[,i]=c("-","-","-")}}
names(infor4)=variable
rownames(infor4)=c("SQ_tr","SQ_bl","SQ_r")
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
norm[,i]=" "}}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
homog[,i]=" "}}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(infor,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(infor,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(infor,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(infor,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(infor,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
# if(design=="DQL"){
# nlinhas=length(analysis$plot$dadosm$groups)
# infor=data.frame(matrix(ncol=length(analysis),nrow = nlinhas))
# trats=analysis[[1]][[1]]$plot$dadosm$trats
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# letra=analysis[[i]][[1]]$plot$dadosm$groups
# transf=analysis[[i]][[1]]$plot$transf
# if(transf==1){media=round(analysis[[i]][[1]]$plot$dadosm$resp,round)}
# if(transf!=1){media=round(analysis[[i]][[1]]$plot$dadosm$respO,round)}
# infor[,i]=paste(media,letra)
# }
# names(infor)=variable
# rownames(infor)=trats
# cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# cvs[,i]=round(sqrt(analysis[[i]][[1]]$plot$a$`Mean Sq`[4])/
# mean(analysis[[i]][[1]]$plot$resp)*100,round)
# }
# rownames(cvs)="CV(%)"
# names(cvs)=variable
#
# transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# tran=analysis[[i]][[1]]$plot$transf
# if(tran==1){tran=1}else{tran=tran}
# if(tran==0){tran="log"}
# if(tran==0.5){tran="sqrt(x)"}
# if(tran==-0.5){tran="1/sqrt(x)"}
# if(tran==-1){tran="1/x"}
# transf[,i]=ifelse(tran==1,"No transf",tran)}
# rownames(transf)="Transformation"
# names(transf)=variable
#
# n=5
# nc=3
# infor1=data.frame(matrix(ncol=length(analysis),nrow = 3))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# pvalor=round(analysis[[i]][[1]]$plot$anava[1:nc,n],round)
# infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
# names(infor1)=variable
# rownames(infor1)=c("p_tr","p_l","p_c")
#
# n=4
# nc=3
# infor2=data.frame(matrix(ncol=length(analysis),nrow = 3))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# infor2[,i]=round(analysis[[i]][[1]]$plot$anava[1:nc,n],round)}
# names(infor2)=variable
# rownames(infor2)=c("F_tr","F_l","F_c")
# n=3
# nc=4
# infor3=data.frame(matrix(ncol=length(analysis),nrow = 4))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# infor3[,i]=round(analysis[[i]][[1]]$plot$anava[1:nc,n],round)}
# names(infor3)=variable
# rownames(infor3)=c("QM_tr","QM_l","QM_c","QM_r")
# n=2
# nc=4
# infor4=data.frame(matrix(ncol=length(analysis),nrow = 4))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# infor4[,i]=round(analysis[[i]][[1]]$plot$anava[1:nc,n],round)}
# names(infor4)=variable
# rownames(infor4)=c("SQ_tr","SQ_l","SQ_c","SQ_r")
# ##############################################
# # normalidade
# ##############################################
# norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
# if(tests=="parametric"){
# variable[i]=analysis[[i]]$plot$labels$y
# norm[,i]=round(analysis[[i]][[1]]$plot$norm1$p.value,round)}
# if(tests=="noparametric"){
# variable[i]=analysis[[i]]$plot$labels$y
# norm[,i]=" "}}
# rownames(norm)="p-value Normality of errors"
# names(norm)=variable
#
# ##############################################
# # homogeneidade
# ##############################################
# homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
# if(tests=="parametric"){
# variable[i]=analysis[[i]]$plot$labels$y
# homog[,i]=round(analysis[[i]][[1]]$plot$homog1$p.value,round)}
# if(tests=="noparametric"){
# variable[i]=analysis[[i]]$plot$labels$y
# homog[,i]=" "}}
# rownames(homog)="p-value Homogeneity of variances"
# names(homog)=variable
#
# if(inf=="p"){juntos=rbind(infor,cvs,infor1,transf,norm,homog)}
# if(inf=="f"){juntos=rbind(infor,cvs,infor2,transf,norm,homog)}
# if(inf=="QM"){juntos=rbind(infor,cvs,infor3,transf,norm,homog)}
# if(inf=="SQ"){juntos=rbind(infor,cvs,infor4,transf,norm,homog)}
# if(inf=="all"){juntos=rbind(infor,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
#
# if(divisor==TRUE){
# nl=nrow(juntos)
# nc=ncol(juntos)
# market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
# juntosnovo=cbind("|"=rep("|",nl),juntos,market)
# for(i in 1:nc){
# ordem=matrix(1:(nc*2),nrow=2)
# nomes=colnames(juntos)
# juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
# colnames(juntosnovo)[1]="|"
# colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
# juntos=juntosnovo}
# }
if(design=="FAT2DIC"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[,i]=round(sqrt(analysis[[i]]$anova$QM[4])/
mean(analysis[[i]]$resp)*100,round)}
rownames(cvs)="CV(%)"
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=3
infor1=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[1:nc,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_F1xF2")
n=4
nc=3
infor2=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_F1xF2")
n=3
nc=4
infor3=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_F2","QM_F1xF2","QM_r")
n=2
nc=4
infor4=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_F2","SQ_F1xF2","SQ_r")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[2,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[1:3,5],round)
if(pvalue[3]<sigF){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<sigF){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<sigF){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
# juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf)
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="FAT2DBC"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[,i]=round(sqrt(analysis[[i]]$anova$QM[5])/
mean(analysis[[i]]$resp)*100,round)}
rownames(cvs)="CV(%)"
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=4
infor1=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[1:nc,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_bl","p_F1xF2")
n=4
nc=4
infor2=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_bl","f_F1xF2")
n=3
nc=5
infor3=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_F2","QM_bl","QM_F1xF2","QM_r")
n=2
nc=5
infor4=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_F2","SQ_bl","SQ_F1xF2","SQ_r")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[2,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[1:4,5],round)
if(pvalue[4]<sigF){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<sigF){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<sigF){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="PSUBDIC"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[1,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[2])/
mean(analysis[[i]]$resp)*100,round)
cvs[2,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[5])/
mean(analysis[[i]]$resp)*100,round)}
rownames(cvs)=c("CV1 (%)","CV2 (%)")
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
# p-value
n=5
infor1=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[c(1,3,4),n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_F1xF2")
n=4
infor2=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[c(1,3,4),n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_F1xF2")
n=3
infor3=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[c(1:5),n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_error1","QM_F2","QM_F1xF2","QM_error2")
n=2
infor4=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:5,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_error1","SQ_F2","SQ_F1xF2","SQ_error2")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[3,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[c(1,3,4),5],round)
if(pvalue[3]<0.05){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<0.05){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<0.05){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="PSUBDBC"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[1,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[3])/
mean(analysis[[i]]$resp)*100,round)
cvs[2,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[6])/
mean(analysis[[i]]$resp)*100,round)}
rownames(cvs)=c("CV1 (%)","CV2 (%)")
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
# p-value
n=5
infor1=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[c(1,2,4,5),n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_bl","p_F2","p_F1xF2")
n=4
infor2=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[c(1,2,4,5),n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_bl","f_F2","f_F1xF2")
n=3
infor3=data.frame(matrix(ncol=length(analysis),nrow = 6))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[c(1:6),n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_bl","QM_error1","QM_F2","QM_F1xF2","QM_error2")
n=2
infor4=data.frame(matrix(ncol=length(analysis),nrow = 6))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:6,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_bl","SQ_error1","SQ_F2","SQ_F1xF2","SQ_error2")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[4,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[c(1,4,5),5],round)
if(pvalue[3]<0.05){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<0.05){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]][[2]]$data)}
if(pvalue[2]<0.05){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="FAT2DBC.ad"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[6])/
mean(c(analysis[[i]]$resp,
analysis[[i]]$respAd))*100,round)}
rownames(cvs)="CV(%)"
names(cvs)=variable
respAd=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
respAd[1,i]=round(mean(analysis[[i]]$resp),round)
respAd[2,i]=round(mean(analysis[[i]]$respAd),round)}
rownames(respAd)=c("Factorial","RespAd")
names(respAd)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=5
infor1=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[1:nc,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_bl","p_F1xF2","p_Fat x Ad")
n=4
nc=5
infor2=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_bl","f_F1xF2","f_Fat x Ad")
n=3
nc=6
infor3=data.frame(matrix(ncol=length(analysis),nrow = 6))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_F2","SQ_bl","QM_F1xF2","QM_Fat x Ad","QM_r")
n=2
nc=6
infor4=data.frame(matrix(ncol=length(analysis),nrow = 6))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_F2","SQ_bl","SQ_F1xF2","SQ_Fat x Ad","SQ_r")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[2,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[1:4,5],round)
if(pvalue[4]<sigF){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<sigF){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<sigF){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,respAd,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,respAd,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,respAd,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,respAd,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,respAd,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="FAT2DIC.ad"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[5])/
mean(c(analysis[[i]]$resp,
analysis[[i]]$respAd))*100,round)}
rownames(cvs)="CV(%)"
names(cvs)=variable
respAd=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
respAd[1,i]=round(mean(analysis[[i]]$resp),round)
respAd[2,i]=round(mean(analysis[[i]]$respAd),round)}
rownames(respAd)=c("Factorial","RespAd")
names(respAd)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=4
infor1=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[1:4,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_F1xF2","p_Fat x Ad")
n=4
nc=4
infor2=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_F1xF2", "f_Fat x Ad")
n=3
nc=5
infor3=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_F2","QM_F1xF2","QM_Fat x Ad","QM_r")
n=2
nc=5
infor4=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_F2","SQ_F1xF2","SQ_Fat x Ad","SQ_r")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[2,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[1:3,5],round)
if(pvalue[3]<sigF){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<sigF){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<sigF){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,respAd,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,respAd,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,respAd,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,respAd,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,respAd,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
# if(design=="dunnett"){
# nlinhas=length(analysis[[1]]$plot$teste[,1])
# trats=rownames(analysis[[1]]$plot$data)
# infor=data.frame(matrix(ncol=length(analysis),nrow = nlinhas))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$label
# infor[i]=analysis[[i]]$plot$teste[6]}
# names(infor)=variable
# rownames(infor)=trats
# juntos=infor}
# print(juntos)
list(juntos)[[1]]
}
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Defines functions summarise_anova
Documented in summarise_anova
#' Utils: Summary of Analysis of Variance and Test of Means
#'
#' @description Summarizes the output of the analysis of variance and the multiple comparisons test for completely randomized (DIC), randomized block (DBC) and Latin square (DQL) designs.
#' @author Gabriel Danilo Shimizu, \email{gabrield.shimizu@gmail.com}
#' @param analysis List with the analysis outputs of the DIC, DBC, DQL, FAT2DIC, FAT2DBC, PSUBDIC and PSUBDBC functions
#' @param design Type of experimental project (DIC, DBC, DQL, FAT2DIC, FAT2DBC, PSUBDIC or PSUBDBC)
#' @param round Number of decimal places
#' @param divisor Add divider between columns
#' @param inf Analysis of variance information (can be "p", "f", "QM" or "SQ")
#' @note Adding table divider can help to build tables in microsoft word. Copy console output, paste into MS Word, Insert, Table, Convert text to table, Separated text into:, Other: |.
#' @note The column names in the final output are imported from the ylab argument within each function.
#' @note This function is only for declared qualitative factors. In the case of a quantitative factor and the other qualitative in projects with two factors, this function will not work.
#' @note Triple factorials and split-split-plot do not work in this function.
#' @return returns a data.frame or print with a summary of the analysis of several experimental projects.
#' @import knitr
#' @export
#' @examples
#'
#'
#' library(AgroR)
#'
#' #=====================================
#' # DIC
#' #=====================================
#' data(pomegranate)
#' attach(pomegranate)
#' a=DIC(trat, WL, geom = "point", ylab = "WL")
#' b=DIC(trat, SS, geom = "point", ylab="SS")
#' c=DIC(trat, AT, geom = "point", ylab = "AT")
#' summarise_anova(analysis = list(a,b,c), divisor = TRUE)
#' library(knitr)
#' kable(summarise_anova(analysis = list(a,b,c), divisor = FALSE))
#'
#' #=====================================
#' vari=c("WL","SS","AT")
#' output=lapply(vari,function(x){
#' output=DIC(trat,response = unlist(pomegranate[,x]),ylab = parse(text=x),print.on=FALSE)})
#' summarise_anova(analysis = output, divisor = TRUE)
#'
#' #=====================================
#' # DBC
#' #=====================================
#' data(soybean)
#' attach(soybean)
#' a=DBC(cult,bloc,prod,ylab = "Yield")
#' summarise_anova(list(a),design = "DBC")
#'
#' #=====================================
#' # FAT2DIC
#' #=====================================
#' data(corn)
#' attach(corn)
#' a=FAT2DIC(A, B, Resp, quali=c(TRUE, TRUE))
#' summarise_anova(list(a),design="FAT2DIC")
summarise_anova=function(analysis,
inf="p",
design="DIC",
round=3,
divisor=FALSE){
requireNamespace("knitr")
if(design=="DIC"){
nlinhas=length(analysis[[1]]$dadosm$groups)
infor=data.frame(matrix(ncol=length(analysis),nrow = nlinhas))
trats=analysis[[1]]$dadosm$trats
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
letra=analysis[[i]]$dadosm$groups
transf=analysis[[i]]$transf
if(transf==1){media=round(analysis[[i]]$dadosm$resp,round)}
if(transf!=1){media=round(analysis[[i]]$dadosm$respO,round)}
infor[,i]=paste(media,letra)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
letra=analysis[[i]]$dadosm$groups
media=round(analysis[[i]]$dadosm$media,round)
infor[,i]=paste(media,letra)}
}
names(infor)=variable
rownames(infor)=trats
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
cvs[,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[2])/
mean(analysis[[i]]$resp)*100,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
cvs[,i]=" "}}
rownames(cvs)="CV(%)"
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
variable[i]=analysis[[i]]$plot$labels$y
if(tests=="parametric"){
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
if(tests=="noparametric"){
transf[,i]=""}
}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=1
infor1=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
pvalor=round(analysis[[i]]$anova[1,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
pvalor=round(analysis[[i]]$krusk$statistics[2],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}}
names(infor1)=variable
rownames(infor1)="p-value"
n=4
nc=1
infor2=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor2[,i]=round(analysis[[i]]$anova[1,n],round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor2[,i]=paste(round(analysis[[i]]$krusk$statistics[1][[1]],round),
"(Chisq)")}}
names(infor2)=variable
rownames(infor2)="F"
n=3
nc=2
infor3=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor3[,i]=""}
}
names(infor3)=variable
rownames(infor3)=c("QM_tr","QM_r")
n=2
nc=2
infor4=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor4[,i]=""}}
names(infor4)=variable
rownames(infor4)=c("SQ_tr","SQ_r")
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
norm[,i]=" "}}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
homog[,i]=" "}}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(infor,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(infor,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(infor,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(infor,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(infor,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="DBC"){
nlinhas=length(analysis[[1]]$dadosm$groups)
infor=data.frame(matrix(ncol=length(analysis),nrow = nlinhas))
trats=analysis[[1]]$dadosm$trats
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
letra=analysis[[i]]$dadosm$groups
transf=analysis[[i]]$transf
if(transf==1){media=round(analysis[[i]]$dadosm$resp,round)}
if(transf!=1){media=round(analysis[[i]]$dadosm$respO,round)}
infor[,i]=paste(media,letra)}
if(tests=="noparametric"){
letra=analysis[[i]]$dadosm$groups
media=round(analysis[[i]]$dadosm$media,round)
infor[,i]=paste(media,letra)}
}
names(infor)=variable
rownames(infor)=trats
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
cvs[,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[3])/
mean(analysis[[i]]$resp)*100,round)}
if(tests=="noparametric"){
cvs[,i]="-"}}
rownames(cvs)="CV(%)"
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
if(tests=="noparametric"){transf[,i]="-"}}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=2
infor1=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
pvalor=round(analysis[[i]]$anova[1:2,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
if(tests=="noparametric"){
pvalor=round(analysis[[i]]$fried$p.F,round)
infor1[,i]=c(ifelse(pvalor<0.001,"p<0.001",pvalor),
"-")}
}
names(infor1)=variable
rownames(infor1)=c("p_tr","p_bl")
n=4
nc=2
infor2=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
infor2[,i]=round(analysis[[i]]$anova[1:2,n],round)}
if(tests=="noparametric"){
infor2[,i]=c(round(analysis[[i]]$fried$`F`,round),
"-")}}
names(infor2)=variable
rownames(infor2)=c("F_tr","F_bl")
n=3
nc=3
infor3=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
infor3[,i]=c("-","-","-")}
}
names(infor3)=variable
rownames(infor3)=c("QM_tr","QM_bl","QM_r")
n=2
nc=3
infor4=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$plot$labels$y
tests=analysis[[i]]$test
if(tests=="parametric"){
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
if(tests=="noparametric"){
infor4[,i]=c("-","-","-")}}
names(infor4)=variable
rownames(infor4)=c("SQ_tr","SQ_bl","SQ_r")
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
norm[,i]=" "}}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
tests=analysis[[i]]$test
if(tests=="parametric"){
variable[i]=analysis[[i]]$plot$labels$y
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
if(tests=="noparametric"){
variable[i]=analysis[[i]]$plot$labels$y
homog[,i]=" "}}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(infor,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(infor,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(infor,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(infor,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(infor,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
# if(design=="DQL"){
# nlinhas=length(analysis$plot$dadosm$groups)
# infor=data.frame(matrix(ncol=length(analysis),nrow = nlinhas))
# trats=analysis[[1]][[1]]$plot$dadosm$trats
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# letra=analysis[[i]][[1]]$plot$dadosm$groups
# transf=analysis[[i]][[1]]$plot$transf
# if(transf==1){media=round(analysis[[i]][[1]]$plot$dadosm$resp,round)}
# if(transf!=1){media=round(analysis[[i]][[1]]$plot$dadosm$respO,round)}
# infor[,i]=paste(media,letra)
# }
# names(infor)=variable
# rownames(infor)=trats
# cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# cvs[,i]=round(sqrt(analysis[[i]][[1]]$plot$a$`Mean Sq`[4])/
# mean(analysis[[i]][[1]]$plot$resp)*100,round)
# }
# rownames(cvs)="CV(%)"
# names(cvs)=variable
#
# transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# tran=analysis[[i]][[1]]$plot$transf
# if(tran==1){tran=1}else{tran=tran}
# if(tran==0){tran="log"}
# if(tran==0.5){tran="sqrt(x)"}
# if(tran==-0.5){tran="1/sqrt(x)"}
# if(tran==-1){tran="1/x"}
# transf[,i]=ifelse(tran==1,"No transf",tran)}
# rownames(transf)="Transformation"
# names(transf)=variable
#
# n=5
# nc=3
# infor1=data.frame(matrix(ncol=length(analysis),nrow = 3))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# pvalor=round(analysis[[i]][[1]]$plot$anava[1:nc,n],round)
# infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
# names(infor1)=variable
# rownames(infor1)=c("p_tr","p_l","p_c")
#
# n=4
# nc=3
# infor2=data.frame(matrix(ncol=length(analysis),nrow = 3))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# infor2[,i]=round(analysis[[i]][[1]]$plot$anava[1:nc,n],round)}
# names(infor2)=variable
# rownames(infor2)=c("F_tr","F_l","F_c")
# n=3
# nc=4
# infor3=data.frame(matrix(ncol=length(analysis),nrow = 4))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# infor3[,i]=round(analysis[[i]][[1]]$plot$anava[1:nc,n],round)}
# names(infor3)=variable
# rownames(infor3)=c("QM_tr","QM_l","QM_c","QM_r")
# n=2
# nc=4
# infor4=data.frame(matrix(ncol=length(analysis),nrow = 4))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$labels$y
# infor4[,i]=round(analysis[[i]][[1]]$plot$anava[1:nc,n],round)}
# names(infor4)=variable
# rownames(infor4)=c("SQ_tr","SQ_l","SQ_c","SQ_r")
# ##############################################
# # normalidade
# ##############################################
# norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
# if(tests=="parametric"){
# variable[i]=analysis[[i]]$plot$labels$y
# norm[,i]=round(analysis[[i]][[1]]$plot$norm1$p.value,round)}
# if(tests=="noparametric"){
# variable[i]=analysis[[i]]$plot$labels$y
# norm[,i]=" "}}
# rownames(norm)="p-value Normality of errors"
# names(norm)=variable
#
# ##############################################
# # homogeneidade
# ##############################################
# homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
# if(tests=="parametric"){
# variable[i]=analysis[[i]]$plot$labels$y
# homog[,i]=round(analysis[[i]][[1]]$plot$homog1$p.value,round)}
# if(tests=="noparametric"){
# variable[i]=analysis[[i]]$plot$labels$y
# homog[,i]=" "}}
# rownames(homog)="p-value Homogeneity of variances"
# names(homog)=variable
#
# if(inf=="p"){juntos=rbind(infor,cvs,infor1,transf,norm,homog)}
# if(inf=="f"){juntos=rbind(infor,cvs,infor2,transf,norm,homog)}
# if(inf=="QM"){juntos=rbind(infor,cvs,infor3,transf,norm,homog)}
# if(inf=="SQ"){juntos=rbind(infor,cvs,infor4,transf,norm,homog)}
# if(inf=="all"){juntos=rbind(infor,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
#
# if(divisor==TRUE){
# nl=nrow(juntos)
# nc=ncol(juntos)
# market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
# juntosnovo=cbind("|"=rep("|",nl),juntos,market)
# for(i in 1:nc){
# ordem=matrix(1:(nc*2),nrow=2)
# nomes=colnames(juntos)
# juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
# colnames(juntosnovo)[1]="|"
# colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
# juntos=juntosnovo}
# }
if(design=="FAT2DIC"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[,i]=round(sqrt(analysis[[i]]$anova$QM[4])/
mean(analysis[[i]]$resp)*100,round)}
rownames(cvs)="CV(%)"
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=3
infor1=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[1:nc,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_F1xF2")
n=4
nc=3
infor2=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_F1xF2")
n=3
nc=4
infor3=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_F2","QM_F1xF2","QM_r")
n=2
nc=4
infor4=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_F2","SQ_F1xF2","SQ_r")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[2,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[1:3,5],round)
if(pvalue[3]<sigF){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<sigF){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<sigF){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
# juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf)
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="FAT2DBC"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[,i]=round(sqrt(analysis[[i]]$anova$QM[5])/
mean(analysis[[i]]$resp)*100,round)}
rownames(cvs)="CV(%)"
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=4
infor1=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[1:nc,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_bl","p_F1xF2")
n=4
nc=4
infor2=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_bl","f_F1xF2")
n=3
nc=5
infor3=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_F2","QM_bl","QM_F1xF2","QM_r")
n=2
nc=5
infor4=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_F2","SQ_bl","SQ_F1xF2","SQ_r")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[2,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[1:4,5],round)
if(pvalue[4]<sigF){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<sigF){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<sigF){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="PSUBDIC"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[1,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[2])/
mean(analysis[[i]]$resp)*100,round)
cvs[2,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[5])/
mean(analysis[[i]]$resp)*100,round)}
rownames(cvs)=c("CV1 (%)","CV2 (%)")
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
# p-value
n=5
infor1=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[c(1,3,4),n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_F1xF2")
n=4
infor2=data.frame(matrix(ncol=length(analysis),nrow = 3))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[c(1,3,4),n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_F1xF2")
n=3
infor3=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[c(1:5),n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_error1","QM_F2","QM_F1xF2","QM_error2")
n=2
infor4=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:5,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_error1","SQ_F2","SQ_F1xF2","SQ_error2")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[3,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[c(1,3,4),5],round)
if(pvalue[3]<0.05){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<0.05){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<0.05){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="PSUBDBC"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[1,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[3])/
mean(analysis[[i]]$resp)*100,round)
cvs[2,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[6])/
mean(analysis[[i]]$resp)*100,round)}
rownames(cvs)=c("CV1 (%)","CV2 (%)")
names(cvs)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
# p-value
n=5
infor1=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[c(1,2,4,5),n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_bl","p_F2","p_F1xF2")
n=4
infor2=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[c(1,2,4,5),n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_bl","f_F2","f_F1xF2")
n=3
infor3=data.frame(matrix(ncol=length(analysis),nrow = 6))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[c(1:6),n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_bl","QM_error1","QM_F2","QM_F1xF2","QM_error2")
n=2
infor4=data.frame(matrix(ncol=length(analysis),nrow = 6))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:6,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_bl","SQ_error1","SQ_F2","SQ_F1xF2","SQ_error2")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[4,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[c(1,4,5),5],round)
if(pvalue[3]<0.05){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<0.05){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]][[2]]$data)}
if(pvalue[2]<0.05){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="FAT2DBC.ad"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[6])/
mean(c(analysis[[i]]$resp,
analysis[[i]]$respAd))*100,round)}
rownames(cvs)="CV(%)"
names(cvs)=variable
respAd=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
respAd[1,i]=round(mean(analysis[[i]]$resp),round)
respAd[2,i]=round(mean(analysis[[i]]$respAd),round)}
rownames(respAd)=c("Factorial","RespAd")
names(respAd)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=5
infor1=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[1:nc,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_bl","p_F1xF2","p_Fat x Ad")
n=4
nc=5
infor2=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_bl","f_F1xF2","f_Fat x Ad")
n=3
nc=6
infor3=data.frame(matrix(ncol=length(analysis),nrow = 6))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_F2","SQ_bl","QM_F1xF2","QM_Fat x Ad","QM_r")
n=2
nc=6
infor4=data.frame(matrix(ncol=length(analysis),nrow = 6))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_F2","SQ_bl","SQ_F1xF2","SQ_Fat x Ad","SQ_r")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[2,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[1:4,5],round)
if(pvalue[4]<sigF){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<sigF){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<sigF){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,respAd,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,respAd,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,respAd,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,respAd,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,respAd,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
if(design=="FAT2DIC.ad"){
cvs=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
cvs[,i]=round(sqrt(analysis[[i]]$anova$`Mean Sq`[5])/
mean(c(analysis[[i]]$resp,
analysis[[i]]$respAd))*100,round)}
rownames(cvs)="CV(%)"
names(cvs)=variable
respAd=data.frame(matrix(ncol=length(analysis),nrow = 2))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
respAd[1,i]=round(mean(analysis[[i]]$resp),round)
respAd[2,i]=round(mean(analysis[[i]]$respAd),round)}
rownames(respAd)=c("Factorial","RespAd")
names(respAd)=variable
transf=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
tran=analysis[[i]]$transf
if(tran==1){tran=1}else{tran=tran}
if(tran==0){tran="log"}
if(tran==0.5){tran="sqrt(x)"}
if(tran==-0.5){tran="1/sqrt(x)"}
if(tran==-1){tran="1/x"}
transf[,i]=ifelse(tran==1,"No transf",tran)}
rownames(transf)="Transformation"
names(transf)=variable
n=5
nc=4
infor1=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
pvalor=round(analysis[[i]]$anova[1:4,n],round)
infor1[,i]=ifelse(pvalor<0.001,"p<0.001",pvalor)}
names(infor1)=variable
rownames(infor1)=c("p_F1","p_F2","p_F1xF2","p_Fat x Ad")
n=4
nc=4
infor2=data.frame(matrix(ncol=length(analysis),nrow = 4))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor2[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor2)=variable
rownames(infor2)=c("f_F1","f_F2","f_F1xF2", "f_Fat x Ad")
n=3
nc=5
infor3=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor3[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor3)=variable
rownames(infor3)=c("QM_F1","QM_F2","QM_F1xF2","QM_Fat x Ad","QM_r")
n=2
nc=5
infor4=data.frame(matrix(ncol=length(analysis),nrow = 5))
variable=1:length(analysis)
for(i in 1:length(analysis)){
variable[i]=analysis[[i]]$ylab
infor4[,i]=round(analysis[[i]]$anova[1:nc,n],round)}
names(infor4)=variable
rownames(infor4)=c("SQ_F1","SQ_F2","SQ_F1xF2","SQ_Fat x Ad","SQ_r")
variable=1:length(analysis)
nf1=analysis[[1]]$anova[1,1]+1
nf2=analysis[[1]]$anova[2,1]+1
nf1f2=nf1*nf2
f1mean=data.frame(matrix(rep("-",(length(analysis)*nf1)),ncol=length(analysis),nrow = nf1))
f2mean=data.frame(matrix(rep("-",(length(analysis)*nf2)),ncol=length(analysis),nrow = nf2))
f1f2mean=data.frame(matrix(rep("-",(length(analysis)*nf1f2)),ncol=length(analysis),nrow = nf1f2))
rownames(f1mean)=unique(analysis[[1]]$f1)
rownames(f2mean)=unique(analysis[[1]]$f2)
nomes=expand.grid(unique(analysis[[1]]$f2),unique(analysis[[1]]$f1))
rownames(f1f2mean)=paste(nomes$Var2,nomes$Var1)
for(i in 1:length(analysis)){
sigF=analysis[[i]]$alpha.f
variable[i]=analysis[[i]]$ylab
pvalue=round(analysis[[i]]$anova[1:3,5],round)
if(pvalue[3]<sigF){f1f2mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$numero)
rownames(f1f2mean)=rownames(analysis[[i]]$plot[[2]]$data)}else{
if(pvalue[1]<sigF){f1mean[,i]=data.frame(analysis[[i]]$plot[[2]]$data$letra)
rownames(f1mean)=rownames(analysis[[i]]$plot[[2]]$data)}
if(pvalue[2]<sigF){f2mean[,i]=data.frame(toupper(analysis[[i]]$plot[[3]]$data$letra))
rownames(f2mean)=rownames(analysis[[i]]$plot[[3]]$data)}}
}
names(f1mean)=variable
names(f2mean)=variable
names(f1f2mean)=variable
##############################################
# normalidade
##############################################
norm=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
norm[,i]=round(analysis[[i]]$norm$p.value,round)}
rownames(norm)="p-value Normality of errors"
names(norm)=variable
##############################################
# homogeneidade
##############################################
homog=data.frame(matrix(ncol=length(analysis),nrow = 1))
variable=1:length(analysis)
for(i in 1:length(analysis)){
# tests=analysis[[i]][[1]]$plot$test
variable[i]=analysis[[i]]$ylab
homog[,i]=round(analysis[[i]]$homog$p.value,round)}
rownames(homog)="p-value Homogeneity of variances"
names(homog)=variable
if(inf=="p"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,respAd,transf,norm,homog)}
if(inf=="f"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor2,respAd,transf,norm,homog)}
if(inf=="QM"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor3,respAd,transf,norm,homog)}
if(inf=="SQ"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor4,respAd,transf,norm,homog)}
if(inf=="all"){juntos=rbind(f1mean,f2mean,f1f2mean,cvs,infor1,infor2,infor3,infor4,respAd,transf,norm,homog)}
if(divisor==TRUE){
nl=nrow(juntos)
nc=ncol(juntos)
market=data.frame(matrix(rep("|",nl*nc),ncol=nc,nrow = nl))
juntosnovo=cbind("|"=rep("|",nl),juntos,market)
for(i in 1:nc){
ordem=matrix(1:(nc*2),nrow=2)
nomes=colnames(juntos)
juntosnovo[,c(ordem[,i]+1)]=cbind(juntos[,i],market[,i])
colnames(juntosnovo)[1]="|"
colnames(juntosnovo)[c(ordem[,i]+1)]=c(nomes[i],"|")}
juntos=juntosnovo}
}
# if(design=="dunnett"){
# nlinhas=length(analysis[[1]]$plot$teste[,1])
# trats=rownames(analysis[[1]]$plot$data)
# infor=data.frame(matrix(ncol=length(analysis),nrow = nlinhas))
# variable=1:length(analysis)
# for(i in 1:length(analysis)){
# variable[i]=analysis[[i]]$plot$label
# infor[i]=analysis[[i]]$plot$teste[6]}
# names(infor)=variable
# rownames(infor)=trats
# juntos=infor}
# print(juntos)
list(juntos)[[1]]
}
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