Nothing
inst/test.R
In ClinReport: Statistical Reporting for Scientific Publications, Epidemiological Studies and Clinical Trials
#
# Author: jfcollin
###############################################################################
#source("C:\\Users\\jfcollin\\git\\inst\\test.R)
##############################################
#Test
##############################################
library(ClinReport)
#####################
# Import libraries
#####################
library(officer)
library(flextable)
library(reshape2)
library(emmeans)
library(lme4)
library(nlme)
library(ggplot2)
library(car)
library(xtable)
#####################
# Load data
#####################
data(datafake)
head(data)
# Removing baseline data for the model
data.mod=droplevels(data[data$TIMEPOINT!="D0",])
#####################
# Create your stats tables and graphics
#####################
# Quatitative stats (2 explicative variables) ##################################
# since it's a big enough table, we don't want it to overlap 2 pasges
# so we split it in two with split.desc function
tab1=report.quanti(data=data,y="y_numeric",
x1="GROUP",x2="TIMEPOINT",at.row="TIMEPOINT",subjid="SUBJID")
s=split(tab1,variable="TIMEPOINT",at=3)
tab1.1=s$x1
tab1.2=s$x2
gg=plot(tab1,title="Mean response evolution as a function of time by treatment group",
legend.label="Treatment groups",ylab="Y mean")
# Qualitative stats (2 explicative variables) ##################################
tab2=report.quali(data=data,y="y_logistic",
x1="GROUP",x2="TIMEPOINT",at.row="TIMEPOINT",total=T,subjid="SUBJID")
gg2=plot(tab2,title="Response distribution (%) by day and treatment group",
legend.label="Y levels")
# Qualitative stats (no explicative variable) ###################################
tab3=report.quali(data=data,y="VAR",y.label="Whatever")
# Qualitative stats (no explicative variables ; add number of subjects in header)#
tab4=report.quali(data=data,y="VAR",y.label="Whatever",
subjid="SUBJID")
# Qualitative stats (1 explicative variable)#######################################
tab5=report.quali(data=data,y="VAR",y.label="Whatever",x1="GROUP",
subjid="SUBJID")
# Quantitative stats (1 explicative variable)#######################################
tab6=report.quanti(data=data,y="y_numeric",y.label="Whatever 2",x1="GROUP",
subjid="SUBJID")
# Quali-Quanti table
tab5.6=regroup(tab5,tab6)
# Linear model (order 2 interaction): Anova and LS-Means reporting ################
mod1=lm(y_numeric~baseline+GROUP+TIMEPOINT+GROUP*TIMEPOINT,data=data.mod)
test1=emmeans(mod1,~GROUP|TIMEPOINT)
anov1=Anova(mod1)
tab.mod1=report.lsmeans(lsm=test1,x1="GROUP",
x2="TIMEPOINT",at.row="TIMEPOINT",data=data.mod)
gg.mod1=plot(tab.mod1,title="LS-Means response evolution as a function of time\n
by treatment group (95% CI)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
# Linear model (1 group only): Anova and LS-Means and graph reporting ################
mod2=lm(y_numeric~baseline+GROUP,data=data.mod)
anov2=Anova(mod2,type=3)
test2=emmeans(mod2,~GROUP)
tab.mod2=report.lsmeans(lsm=test2,x1="GROUP",data=data.mod)
gg.mod2=plot(tab.mod2,title="LS-Means response\nby treatment group (95% CI)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
# Linear mixed model (order 2 interaction):
# Anova and LS-Means and graph reporting #################
mod3=lme(y_numeric~baseline+GROUP+TIMEPOINT+GROUP*TIMEPOINT,
random=~1|SUBJID,data=data.mod,na.action=na.omit)
anov3=Anova(mod3,3)
test3=emmeans(mod3,~GROUP|TIMEPOINT)
tab.mod3=report.lsmeans(lsm=test3,x1="GROUP",
x2="TIMEPOINT",at.row="TIMEPOINT",data=data.mod)
gg.mod3=plot(tab.mod3,title="LS-Means response evolution as a function of time\n
by treatment group (95% CI Mixed model)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
# Contrast example
contr=contrast(test3, "trt.vs.ctrl", ref = "A")
tab.mod3.contr=report.lsmeans(lsm=contr,x1="TIMEPOINT",
data=data.mod,contrast=TRUE,at.row="contrast")
gg.mod3.contr=plot(tab.mod3.contr,title="LS-Means contrast versus reference A\n
(95% CI Mixed model)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T,add.line=F)
# Generalized Logistic Linear model (order 2 interaction):
# Anova LS-Means and graph reporting ##########
mod4=glm(y_logistic~baseline+GROUP+TIMEPOINT+GROUP*TIMEPOINT,
family=binomial,data=data.mod,na.action=na.omit)
anov4=Anova(mod4,3)
test4=emmeans(mod4,~GROUP|TIMEPOINT)
tab.mod4=report.lsmeans(lsm=test4,x1="GROUP",
x2="TIMEPOINT",at.row="TIMEPOINT",data=data.mod)
gg.mod4=plot(tab.mod4,title="LS-Means response evolution as a function of time\n
by treatment group (95% CI Logistic model)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
# Generalized Poisson Linear model (order 2 interaction):
# Anova LS-Means and graph reporting #'
mod5=glm(y_poisson~baseline+GROUP+TIMEPOINT+GROUP*TIMEPOINT,
family=poisson,data=data.mod,na.action=na.omit)
anov5=Anova(mod5,3)
test5=emmeans(mod5,~GROUP|TIMEPOINT)
tab.mod5=report.lsmeans(lsm=test5,x1="GROUP",
x2="TIMEPOINT",at.row="TIMEPOINT",type="response",data=data.mod)
gg.mod5=plot(tab.mod5,title="LS-Means response evolution as a function of time\n
by treatment group (95% CI Poisson model)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
#####################
# Create your report
#####################
doc=read_docx()
doc=body_add_toc(doc)
doc=body_add_par(doc,"A beautiful reporting using ClinReport", style = "heading 1")
doc=body_add_par(doc,"Descriptive statistics", style = "heading 2")
doc=report.doc(tab1.1,title="Quantitative statistics (2 explicative variables) (Table 1/2)",
colspan.value="Treatment group",doc=doc,init.numbering=T,
page.break=F)
doc=report.doc(tab1.2,title="Quantitative statistics (2 explicative variables) (Table 2/2)",
colspan.value="Treatment group",doc=doc)
doc=body_add_par(doc,"Corresponding graphic of outputs 1 & 2", style ="Normal")
doc=body_add_gg(doc, value = gg, style = "centered" )
doc=body_add_break(doc)
doc=report.doc(tab2,title="Qualitative statistics (2 explicative variables)",
colspan.value="Treatment group",doc=doc)
doc=report.doc(tab2,title="The same with smaller font size",
colspan.value="Treatment group",doc=doc,font.size=8)
doc=body_add_par(doc,"Corresponding graphic of output 3", style ="Normal")
doc=body_add_gg(doc, value = gg2, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Example of mixing qualitative and quantitative
statistics with the function regroup", style ="Normal")
doc=report.doc(tab5.6,title="Quali-Qanti statistics (1 variable only)",doc=doc)
doc=body_add_par(doc,"Statistical model results", style = "heading 2")
doc=body_add_par(doc,"Model 1", style = "heading 3")
doc=body_add_par(doc,"Anova table example", style = "Normal")
doc=report.doc(anov1,doc=doc)
doc=body_add_par(doc,"LS-Means example", style = "Normal")
doc=report.doc(tab.mod1,title="Linear Model LS-Means results using lm with interactions",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod1, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Model 2", style = "heading 3")
doc=report.doc(anov2,doc=doc)
doc=report.doc(tab.mod2,title="Linear Model LS-Means results using lm without interaction",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod2, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Model 3", style = "heading 3")
doc=report.doc(anov3,doc=doc)
doc=report.doc(tab.mod3,title="Linear Mixed Model LS-Means results using lme",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod3, style = "centered" )
doc=body_add_break(doc)
doc=report.doc(tab.mod3.contr,title="LS-Means Contrast example",
colspan.value="Timepoints",doc=doc)
doc=body_add_gg(doc, value = gg.mod3.contr, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Model 4", style = "heading 3")
doc=report.doc(anov4,doc=doc)
doc=report.doc(tab.mod4,title="Generalized Linear Mixed Model LS-Means results using glm",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod4, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Model 5", style = "heading 3")
doc=report.doc(anov5,doc=doc)
doc=report.doc(tab.mod5,title="Poisson Model LS-Means results",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod5, style = "centered" )
file=paste(tempfile(),".docx",sep="")
print(doc, target =file)
shell.exec(file)
f=function(a)
{
if(class(substitute(a))=="name")
{
x=as.character(substitute(a))
x
}else
{
a
}
}
Try the ClinReport package in your browser
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ClinReport documentation built on Sept. 3, 2019, 5:07 p.m.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
#
# Author: jfcollin
###############################################################################
#source("C:\\Users\\jfcollin\\git\\inst\\test.R)
##############################################
#Test
##############################################
library(ClinReport)
#####################
# Import libraries
#####################
library(officer)
library(flextable)
library(reshape2)
library(emmeans)
library(lme4)
library(nlme)
library(ggplot2)
library(car)
library(xtable)
#####################
# Load data
#####################
data(datafake)
head(data)
# Removing baseline data for the model
data.mod=droplevels(data[data$TIMEPOINT!="D0",])
#####################
# Create your stats tables and graphics
#####################
# Quatitative stats (2 explicative variables) ##################################
# since it's a big enough table, we don't want it to overlap 2 pasges
# so we split it in two with split.desc function
tab1=report.quanti(data=data,y="y_numeric",
x1="GROUP",x2="TIMEPOINT",at.row="TIMEPOINT",subjid="SUBJID")
s=split(tab1,variable="TIMEPOINT",at=3)
tab1.1=s$x1
tab1.2=s$x2
gg=plot(tab1,title="Mean response evolution as a function of time by treatment group",
legend.label="Treatment groups",ylab="Y mean")
# Qualitative stats (2 explicative variables) ##################################
tab2=report.quali(data=data,y="y_logistic",
x1="GROUP",x2="TIMEPOINT",at.row="TIMEPOINT",total=T,subjid="SUBJID")
gg2=plot(tab2,title="Response distribution (%) by day and treatment group",
legend.label="Y levels")
# Qualitative stats (no explicative variable) ###################################
tab3=report.quali(data=data,y="VAR",y.label="Whatever")
# Qualitative stats (no explicative variables ; add number of subjects in header)#
tab4=report.quali(data=data,y="VAR",y.label="Whatever",
subjid="SUBJID")
# Qualitative stats (1 explicative variable)#######################################
tab5=report.quali(data=data,y="VAR",y.label="Whatever",x1="GROUP",
subjid="SUBJID")
# Quantitative stats (1 explicative variable)#######################################
tab6=report.quanti(data=data,y="y_numeric",y.label="Whatever 2",x1="GROUP",
subjid="SUBJID")
# Quali-Quanti table
tab5.6=regroup(tab5,tab6)
# Linear model (order 2 interaction): Anova and LS-Means reporting ################
mod1=lm(y_numeric~baseline+GROUP+TIMEPOINT+GROUP*TIMEPOINT,data=data.mod)
test1=emmeans(mod1,~GROUP|TIMEPOINT)
anov1=Anova(mod1)
tab.mod1=report.lsmeans(lsm=test1,x1="GROUP",
x2="TIMEPOINT",at.row="TIMEPOINT",data=data.mod)
gg.mod1=plot(tab.mod1,title="LS-Means response evolution as a function of time\n
by treatment group (95% CI)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
# Linear model (1 group only): Anova and LS-Means and graph reporting ################
mod2=lm(y_numeric~baseline+GROUP,data=data.mod)
anov2=Anova(mod2,type=3)
test2=emmeans(mod2,~GROUP)
tab.mod2=report.lsmeans(lsm=test2,x1="GROUP",data=data.mod)
gg.mod2=plot(tab.mod2,title="LS-Means response\nby treatment group (95% CI)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
# Linear mixed model (order 2 interaction):
# Anova and LS-Means and graph reporting #################
mod3=lme(y_numeric~baseline+GROUP+TIMEPOINT+GROUP*TIMEPOINT,
random=~1|SUBJID,data=data.mod,na.action=na.omit)
anov3=Anova(mod3,3)
test3=emmeans(mod3,~GROUP|TIMEPOINT)
tab.mod3=report.lsmeans(lsm=test3,x1="GROUP",
x2="TIMEPOINT",at.row="TIMEPOINT",data=data.mod)
gg.mod3=plot(tab.mod3,title="LS-Means response evolution as a function of time\n
by treatment group (95% CI Mixed model)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
# Contrast example
contr=contrast(test3, "trt.vs.ctrl", ref = "A")
tab.mod3.contr=report.lsmeans(lsm=contr,x1="TIMEPOINT",
data=data.mod,contrast=TRUE,at.row="contrast")
gg.mod3.contr=plot(tab.mod3.contr,title="LS-Means contrast versus reference A\n
(95% CI Mixed model)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T,add.line=F)
# Generalized Logistic Linear model (order 2 interaction):
# Anova LS-Means and graph reporting ##########
mod4=glm(y_logistic~baseline+GROUP+TIMEPOINT+GROUP*TIMEPOINT,
family=binomial,data=data.mod,na.action=na.omit)
anov4=Anova(mod4,3)
test4=emmeans(mod4,~GROUP|TIMEPOINT)
tab.mod4=report.lsmeans(lsm=test4,x1="GROUP",
x2="TIMEPOINT",at.row="TIMEPOINT",data=data.mod)
gg.mod4=plot(tab.mod4,title="LS-Means response evolution as a function of time\n
by treatment group (95% CI Logistic model)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
# Generalized Poisson Linear model (order 2 interaction):
# Anova LS-Means and graph reporting #'
mod5=glm(y_poisson~baseline+GROUP+TIMEPOINT+GROUP*TIMEPOINT,
family=poisson,data=data.mod,na.action=na.omit)
anov5=Anova(mod5,3)
test5=emmeans(mod5,~GROUP|TIMEPOINT)
tab.mod5=report.lsmeans(lsm=test5,x1="GROUP",
x2="TIMEPOINT",at.row="TIMEPOINT",type="response",data=data.mod)
gg.mod5=plot(tab.mod5,title="LS-Means response evolution as a function of time\n
by treatment group (95% CI Poisson model)",
legend.label="Treatment groups",ylab="Y mean",add.ci=T)
#####################
# Create your report
#####################
doc=read_docx()
doc=body_add_toc(doc)
doc=body_add_par(doc,"A beautiful reporting using ClinReport", style = "heading 1")
doc=body_add_par(doc,"Descriptive statistics", style = "heading 2")
doc=report.doc(tab1.1,title="Quantitative statistics (2 explicative variables) (Table 1/2)",
colspan.value="Treatment group",doc=doc,init.numbering=T,
page.break=F)
doc=report.doc(tab1.2,title="Quantitative statistics (2 explicative variables) (Table 2/2)",
colspan.value="Treatment group",doc=doc)
doc=body_add_par(doc,"Corresponding graphic of outputs 1 & 2", style ="Normal")
doc=body_add_gg(doc, value = gg, style = "centered" )
doc=body_add_break(doc)
doc=report.doc(tab2,title="Qualitative statistics (2 explicative variables)",
colspan.value="Treatment group",doc=doc)
doc=report.doc(tab2,title="The same with smaller font size",
colspan.value="Treatment group",doc=doc,font.size=8)
doc=body_add_par(doc,"Corresponding graphic of output 3", style ="Normal")
doc=body_add_gg(doc, value = gg2, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Example of mixing qualitative and quantitative
statistics with the function regroup", style ="Normal")
doc=report.doc(tab5.6,title="Quali-Qanti statistics (1 variable only)",doc=doc)
doc=body_add_par(doc,"Statistical model results", style = "heading 2")
doc=body_add_par(doc,"Model 1", style = "heading 3")
doc=body_add_par(doc,"Anova table example", style = "Normal")
doc=report.doc(anov1,doc=doc)
doc=body_add_par(doc,"LS-Means example", style = "Normal")
doc=report.doc(tab.mod1,title="Linear Model LS-Means results using lm with interactions",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod1, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Model 2", style = "heading 3")
doc=report.doc(anov2,doc=doc)
doc=report.doc(tab.mod2,title="Linear Model LS-Means results using lm without interaction",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod2, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Model 3", style = "heading 3")
doc=report.doc(anov3,doc=doc)
doc=report.doc(tab.mod3,title="Linear Mixed Model LS-Means results using lme",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod3, style = "centered" )
doc=body_add_break(doc)
doc=report.doc(tab.mod3.contr,title="LS-Means Contrast example",
colspan.value="Timepoints",doc=doc)
doc=body_add_gg(doc, value = gg.mod3.contr, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Model 4", style = "heading 3")
doc=report.doc(anov4,doc=doc)
doc=report.doc(tab.mod4,title="Generalized Linear Mixed Model LS-Means results using glm",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod4, style = "centered" )
doc=body_add_break(doc)
doc=body_add_par(doc,"Model 5", style = "heading 3")
doc=report.doc(anov5,doc=doc)
doc=report.doc(tab.mod5,title="Poisson Model LS-Means results",
colspan.value="Treatment group",doc=doc)
doc=body_add_gg(doc, value = gg.mod5, style = "centered" )
file=paste(tempfile(),".docx",sep="")
print(doc, target =file)
shell.exec(file)
f=function(a)
{
if(class(substitute(a))=="name")
{
x=as.character(substitute(a))
x
}else
{
a
}
}
Try the ClinReport package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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