Nothing
ANOVA One-way and Two-way"
In ANOVAShiny2: Interactive Document for Working with Analysis of Variance
knitr::opts_chunk$set(echo = TRUE)
library(dplyr)
library(rhandsontable)
library(DescTools)
```r
options(shiny.maxRequestSize = 100 * 1024^2)
sidebarPanel(
inputPanel(
checkboxInput("ex","Uncheck for using your own file",value = TRUE),
fileInput("file", "Upload the *.csv file with headers"),
uiOutput("vx"),
selectInput("antype","Select Type of ANOVA",choices = c("One-way","Two-way","Factorial"),selected = "One-way"),
downloadButton("downloadPlot", "Download Plot"),
downloadButton("downloaddata2", "Download Example Dataset")
),
inputPanel(
h6("Inputs" ),
uiOutput("vy"),
uiOutput("vxd"),
uiOutput("vxd2")
),
inputPanel(
h6("Mean,SD,n Inputs",width =300),
rHandsontableOutput("testdata"),
downloadButton("downloaddata", "Download Dataset")
)
)
mainPanel(
tabsetPanel(type = "tab",
tabPanel("Model", verbatimTextOutput("AD")),
tabPanel("Visualization", plotOutput("VP")),
tabPanel("Model on aggregate(One-way)",verbatimTextOutput("AN"))
),
h6("", tags$img(src ="K.JPG", height= 400, width=400))
)
output$AD<-renderPrint({
if(input$ex == TRUE)
{data("ToothGrowth")
data = ToothGrowth
data$dose = factor(data$dose)}
else{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
ds = data
ds = select(ds,input$variablex)
cat(sprintf("\nSnapshot of the dataset\n"))
print(head(ds))
options(scipen = 999)
if(input$antype == "One-way")
{
cat(sprintf("\nHypotheses for One-way ANOVA\n"))
cat(sprintf("\nHo :%s of all categories of %s are same\n",input$variabley,input$variablexd))
cat(sprintf("\nHa :%s of not all categories of %s are same\n\n",input$variabley,input$variablexd))
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
fit <- aov(as.formula(mod), data=ds)
print(summary(fit))
cat(sprintf("\nPosthoc tests of Least Significant Difference(LSD)\n"))
print(PostHocTest(fit, method = "lsd", conf.level=NA))
}
if(input$antype == "Two-way")
{
cat(sprintf("\nHypotheses for Two-way ANOVA\n"))
cat(sprintf("\nHo :%s is not influenced by the treatments %s and %s\n",input$variabley,input$variablexd,input$variablexd2))
cat(sprintf("\nHa:%s is influenced by either of the treatments %s and %s\n",input$variabley,input$variablexd,input$variablexd2))
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
mod = paste(mod,"+")
mod = paste(mod,input$variablexd2)
fit <- aov(as.formula(mod), data=ds)
print(summary(fit))
}
if(input$antype == "Factorial")
{
cat(sprintf("\nHypotheses for Factorial Design(Two way ANOVA with interaction)\n"))
cat(sprintf("\nHo :%s is not influenced by the treatments %s and %s and their interaction\n ",input$variabley,input$variablexd,input$variablexd2))
cat(sprintf("\nHa:%s is influenced by either of the treatments %s and %s and their interaction\n",input$variabley,input$variablexd,input$variablexd2))
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
mod = paste(mod,"*")
mod = paste(mod,input$variablexd2)
fit <- aov(as.formula(mod), data=ds)
print(summary(fit))
}
})
output$VP<-renderPlot({
if(input$ex == TRUE)
{data("ToothGrowth")
data = ToothGrowth
data$dose = factor(data$dose)}
else{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
ds = data
ds = select(ds,input$variablex)
options(scipen = 999)
if(input$antype == "One-way")
{
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
boxplot(as.formula(mod),data =ds,col = "red",ylab = input$variabley,xlab =input$variablexd,main = "One-way ANOVA Visualization")
}
if(input$antype == "Two-way")
{
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
mod = paste(mod,"+")
mod = paste(mod,input$variablexd2)
boxplot(as.formula(mod),data =ds,col = "red",xlab ="Treatments",ylab = input$variabley,main = "Two-way ANOVA Visualization ")
}
if(input$antype == "Factorial")
{
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
mod = paste(mod,"*")
mod = paste(mod,input$variablexd2)
# attach(ds)
# interaction.plot(get(input$variablexd),get(input$variablexd2),get(input$variabley#),type ="b",col= c("red","blue"),main = "Interaction between Treatments",xlab = #input$variablexd,ylab = input$variabley,trace.label = input$variablexd2)
HH::interaction2wt(as.formula(mod),data = ds)
}
})
output$vx <- renderUI({
if(input$ex == TRUE)
{data("ToothGrowth")
data = ToothGrowth
data$dose = factor(data$dose)}
else
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
quantdata = select_if(data,is.numeric)
qualdata = select_if(data,is.character)
qualdata = data.frame(lapply(qualdata,as.factor))
data = data.frame(cbind(quantdata,qualdata))
}
checkboxGroupInput("variablex","Select the variables",choices = colnames(data),selected = colnames(data))
})
output$vy <- renderUI({
if(input$ex == TRUE)
{data("ToothGrowth")
data = ToothGrowth
data$dose = factor(data$dose)}
else
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
ds = data
ds = select(ds,input$variablex)
ds = select_if(ds,is.numeric)
selectInput("variabley","Select the dependent variable",choices = colnames(ds),selected = "" )
})
output$vxd <- renderUI({
if(input$ex == TRUE)
{data("ToothGrowth")
data = ToothGrowth
data$dose = factor(data$dose)}
else
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
quantdata = select_if(data,is.numeric)
qualdata = select_if(data,is.character)
qualdata = data.frame(lapply(qualdata,as.factor))
data = data.frame(cbind(quantdata,qualdata))
}
ds = data
ds = select(ds,input$variablex)
ds = select_if(ds,is.factor)
selectInput("variablexd","Select the independent variable",choices = colnames(ds),selected = "" )
})
output$vxd2 <- renderUI({
if(input$ex == TRUE)
{data("ToothGrowth")
data = ToothGrowth
data$dose = factor(data$dose)}
else
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
quantdata = select_if(data,is.numeric)
qualdata = select_if(data,is.character)
qualdata = data.frame(lapply(qualdata,as.factor))
data = data.frame(cbind(quantdata,qualdata))
}
ds = data
ds = select(ds,input$variablex)
ds = select_if(ds,is.factor)
selectInput("variablexd2","Select the 2nd independent variable",choices = colnames(ds),selected = colnames(ds)[2] )
})
output$testdata <- renderRHandsontable({
DF = data.frame(Group=c(1,2,3), mean= c(62,52,60), sd = c(6,5,7), n= c(8,8,7))
rhandsontable(DF)
})
output$AN <- renderPrint({
data_frame = data.frame(hot_to_r(input$testdata))
levels = length(unique(data_frame$n))
data_frame1 = select(data_frame,c(n,mean,sd))
data_frame1$mean = as.numeric(data_frame$mean)
data_frame1$sd = as.numeric(data_frame$sd)
data_frame1$n = as.numeric(data_frame$n)
rnorm2 = function(n,mean,sd) { mean+ sd*scale(rnorm(n)) }
df = mapply(rnorm2,data_frame1[,1],data_frame1[,2],data_frame[,3])
if(levels > 1)
{ attributes(df) = list( names = names(df), row.names=1:max(data_frame$n), class = 'data.frame')
colnames(df) = 1:ncol(df)
df2 =data.frame(values = unlist(df))
row.names(df2)= 1: nrow(df2)
data_frame2 = select(data_frame,c(Group,n))
data_frame2$Group = as.factor(data_frame2$Group)
dataset1 = data_frame2
dataset1 = data.frame(ind = dataset1[rep(seq_len(nrow(dataset1)), dataset1$n) ,1 ])
row.names(dataset1) = 1:nrow(dataset1)
df2$ind = as.factor(dataset1$ind)
}
else
{
df = data.frame(df)
df2 = data.frame(stack(df[1:ncol(df)]))
#print(df2)
}
dataset = df2
print(summary(aov(as.formula(values~ind),data = dataset)))
cat(sprintf("\nPost Hoc tests\n"))
print(PostHocTest(aov(as.formula(values~ind),data = dataset), method = "lsd", conf.level=NA))
})
datasetInput1 <- reactive({
data_frame = data.frame(hot_to_r(input$testdata))
levels = length(unique(data_frame$n))
data_frame1 = select(data_frame,c(n,mean,sd))
data_frame1$mean = as.numeric(data_frame$mean)
data_frame1$sd = as.numeric(data_frame$sd)
data_frame1$n = as.numeric(data_frame$n)
rnorm2 = function(n,mean,sd) { mean+ sd*scale(rnorm(n)) }
df = mapply(rnorm2,data_frame1[,1],data_frame1[,2],data_frame[,3])
if(levels > 1)
{ attributes(df) = list( names = names(df), row.names=1:max(data_frame$n), class = 'data.frame')
colnames(df) = 1:ncol(df)
df2 =data.frame(values = unlist(df))
row.names(df2)= 1: nrow(df2)
data_frame2 = select(data_frame,c(Group,n))
data_frame2$Group = as.factor(data_frame2$Group)
dataset1 = data_frame2
dataset1 = data.frame(ind = dataset1[rep(seq_len(nrow(dataset1)), dataset1$n) ,1 ])
row.names(dataset1) = 1:nrow(dataset1)
df2$ind = as.factor(dataset1$ind)
}
else
{
df = data.frame(df)
df2 = data.frame(stack(df[1:ncol(df)]))
#print(df2)
}
data = df2
})
output$downloaddata <- downloadHandler(
filename = function() {
filetitle = paste("dataset")
paste(filetitle, ".csv", sep = "")
},
content = function(file) {
write.csv(datasetInput1(), file, row.names = FALSE)
}
)
output$downloadPlot<- downloadHandler(
filename = function() {
paste("ANOVAplot", ".png", sep = "")
},
content = function(file) {
png(file)
if(input$ex == TRUE)
{data("ToothGrowth")
data = ToothGrowth
data$dose = factor(data$dose)}
else{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
ds = data
ds = select(ds,input$variablex)
options(scipen = 999)
if(input$antype == "One-way")
{
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
boxplot(as.formula(mod),data =ds,col = "red",ylab = input$variabley,xlab =input$variablexd,main = "One-way ANOVA Visualization")
}
if(input$antype == "Two-way")
{
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
mod = paste(mod,"+")
mod = paste(mod,input$variablexd2)
boxplot(as.formula(mod),data =ds,col = "red",xlab ="Treatments",ylab = input$variabley,main = "Two-way ANOVA Visualization ")
}
if(input$antype == "Factorial")
{
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
mod = paste(mod,"*")
mod = paste(mod,input$variablexd2)
attach(ds)
interaction.plot(get(input$variablexd),get(input$variablexd2),get(input$variabley),type ="b",col= c("red","blue"),main = "Interaction between Treatments",xlab = input$variablexd,ylab = input$variabley,trace.label = input$variablexd2)
}
dev.off()
})
datasetInput2 <- reactive({
data("ToothGrowth")
data = ToothGrowth
data$dose = factor(data$dose)
data = data
})
output$downloaddata2 <- downloadHandler(
filename = function() {
filetitle = paste("Exampledataset")
paste(filetitle, ".csv", sep = "")
},
content = function(file) {
write.csv(datasetInput2(), file, row.names = FALSE)
}
)
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ANOVAShiny2 documentation built on Aug. 27, 2020, 5:09 p.m.
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knitr::opts_chunk$set(echo = TRUE) library(dplyr) library(rhandsontable) library(DescTools)
```r options(shiny.maxRequestSize = 100 * 1024^2) sidebarPanel( inputPanel( checkboxInput("ex","Uncheck for using your own file",value = TRUE), fileInput("file", "Upload the *.csv file with headers"), uiOutput("vx"), selectInput("antype","Select Type of ANOVA",choices = c("One-way","Two-way","Factorial"),selected = "One-way"), downloadButton("downloadPlot", "Download Plot"), downloadButton("downloaddata2", "Download Example Dataset")
),
inputPanel( h6("Inputs" ),
uiOutput("vy"), uiOutput("vxd"), uiOutput("vxd2")
), inputPanel( h6("Mean,SD,n Inputs",width =300), rHandsontableOutput("testdata"), downloadButton("downloaddata", "Download Dataset") )
) mainPanel( tabsetPanel(type = "tab", tabPanel("Model", verbatimTextOutput("AD")), tabPanel("Visualization", plotOutput("VP")), tabPanel("Model on aggregate(One-way)",verbatimTextOutput("AN"))
),
h6("", tags$img(src ="K.JPG", height= 400, width=400)) ) output$AD<-renderPrint({ if(input$ex == TRUE) {data("ToothGrowth") data = ToothGrowth data$dose = factor(data$dose)} else{ file1 = input$file if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
ds = data
ds = select(ds,input$variablex)
cat(sprintf("\nSnapshot of the dataset\n"))
print(head(ds))
options(scipen = 999)
if(input$antype == "One-way")
{
cat(sprintf("\nHypotheses for One-way ANOVA\n"))
cat(sprintf("\nHo :%s of all categories of %s are same\n",input$variabley,input$variablexd))
cat(sprintf("\nHa :%s of not all categories of %s are same\n\n",input$variabley,input$variablexd))
mod = paste(input$variabley,"~") mod = paste(mod,input$variablexd)
fit <- aov(as.formula(mod), data=ds) print(summary(fit)) cat(sprintf("\nPosthoc tests of Least Significant Difference(LSD)\n")) print(PostHocTest(fit, method = "lsd", conf.level=NA)) }
if(input$antype == "Two-way")
{
cat(sprintf("\nHypotheses for Two-way ANOVA\n"))
cat(sprintf("\nHo :%s is not influenced by the treatments %s and %s\n",input$variabley,input$variablexd,input$variablexd2))
cat(sprintf("\nHa:%s is influenced by either of the treatments %s and %s\n",input$variabley,input$variablexd,input$variablexd2))
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
mod = paste(mod,"+")
mod = paste(mod,input$variablexd2)
fit <- aov(as.formula(mod), data=ds) print(summary(fit))
}
if(input$antype == "Factorial")
{
cat(sprintf("\nHypotheses for Factorial Design(Two way ANOVA with interaction)\n"))
cat(sprintf("\nHo :%s is not influenced by the treatments %s and %s and their interaction\n ",input$variabley,input$variablexd,input$variablexd2))
cat(sprintf("\nHa:%s is influenced by either of the treatments %s and %s and their interaction\n",input$variabley,input$variablexd,input$variablexd2))
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd) mod = paste(mod,"*") mod = paste(mod,input$variablexd2)
fit <- aov(as.formula(mod), data=ds) print(summary(fit))
}
})
output$VP<-renderPlot({ if(input$ex == TRUE) {data("ToothGrowth") data = ToothGrowth data$dose = factor(data$dose)} else{ file1 = input$file if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
ds = data
ds = select(ds,input$variablex)
options(scipen = 999)
if(input$antype == "One-way")
{
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
boxplot(as.formula(mod),data =ds,col = "red",ylab = input$variabley,xlab =input$variablexd,main = "One-way ANOVA Visualization")
} if(input$antype == "Two-way")
{ mod = paste(input$variabley,"~") mod = paste(mod,input$variablexd) mod = paste(mod,"+") mod = paste(mod,input$variablexd2) boxplot(as.formula(mod),data =ds,col = "red",xlab ="Treatments",ylab = input$variabley,main = "Two-way ANOVA Visualization ")
}
if(input$antype == "Factorial")
{
mod = paste(input$variabley,"~") mod = paste(mod,input$variablexd) mod = paste(mod,"*") mod = paste(mod,input$variablexd2) # attach(ds) # interaction.plot(get(input$variablexd),get(input$variablexd2),get(input$variabley#),type ="b",col= c("red","blue"),main = "Interaction between Treatments",xlab = #input$variablexd,ylab = input$variabley,trace.label = input$variablexd2)
HH::interaction2wt(as.formula(mod),data = ds) }
})
output$vx <- renderUI({
if(input$ex == TRUE) {data("ToothGrowth") data = ToothGrowth data$dose = factor(data$dose)} else {
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
quantdata = select_if(data,is.numeric)
qualdata = select_if(data,is.character)
qualdata = data.frame(lapply(qualdata,as.factor))
data = data.frame(cbind(quantdata,qualdata))
}
checkboxGroupInput("variablex","Select the variables",choices = colnames(data),selected = colnames(data))
}) output$vy <- renderUI({
if(input$ex == TRUE) {data("ToothGrowth") data = ToothGrowth data$dose = factor(data$dose)} else {
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
ds = data
ds = select(ds,input$variablex)
ds = select_if(ds,is.numeric)
selectInput("variabley","Select the dependent variable",choices = colnames(ds),selected = "" )
}) output$vxd <- renderUI({
if(input$ex == TRUE) {data("ToothGrowth") data = ToothGrowth data$dose = factor(data$dose)} else {
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
quantdata = select_if(data,is.numeric)
qualdata = select_if(data,is.character)
qualdata = data.frame(lapply(qualdata,as.factor))
data = data.frame(cbind(quantdata,qualdata))
}
ds = data
ds = select(ds,input$variablex)
ds = select_if(ds,is.factor)
selectInput("variablexd","Select the independent variable",choices = colnames(ds),selected = "" )
}) output$vxd2 <- renderUI({
if(input$ex == TRUE) {data("ToothGrowth") data = ToothGrowth data$dose = factor(data$dose)} else {
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
quantdata = select_if(data,is.numeric)
qualdata = select_if(data,is.character)
qualdata = data.frame(lapply(qualdata,as.factor))
data = data.frame(cbind(quantdata,qualdata))
}
ds = data
ds = select(ds,input$variablex)
ds = select_if(ds,is.factor)
selectInput("variablexd2","Select the 2nd independent variable",choices = colnames(ds),selected = colnames(ds)[2] )
})
output$testdata <- renderRHandsontable({ DF = data.frame(Group=c(1,2,3), mean= c(62,52,60), sd = c(6,5,7), n= c(8,8,7))
rhandsontable(DF)
})
output$AN <- renderPrint({
data_frame = data.frame(hot_to_r(input$testdata))
levels = length(unique(data_frame$n))
data_frame1 = select(data_frame,c(n,mean,sd)) data_frame1$mean = as.numeric(data_frame$mean) data_frame1$sd = as.numeric(data_frame$sd) data_frame1$n = as.numeric(data_frame$n)
rnorm2 = function(n,mean,sd) { mean+ sd*scale(rnorm(n)) }
df = mapply(rnorm2,data_frame1[,1],data_frame1[,2],data_frame[,3])
if(levels > 1) { attributes(df) = list( names = names(df), row.names=1:max(data_frame$n), class = 'data.frame') colnames(df) = 1:ncol(df)
df2 =data.frame(values = unlist(df)) row.names(df2)= 1: nrow(df2)
data_frame2 = select(data_frame,c(Group,n)) data_frame2$Group = as.factor(data_frame2$Group) dataset1 = data_frame2 dataset1 = data.frame(ind = dataset1[rep(seq_len(nrow(dataset1)), dataset1$n) ,1 ]) row.names(dataset1) = 1:nrow(dataset1)
df2$ind = as.factor(dataset1$ind)
} else
{ df = data.frame(df) df2 = data.frame(stack(df[1:ncol(df)])) #print(df2) } dataset = df2 print(summary(aov(as.formula(values~ind),data = dataset))) cat(sprintf("\nPost Hoc tests\n")) print(PostHocTest(aov(as.formula(values~ind),data = dataset), method = "lsd", conf.level=NA))
})
datasetInput1 <- reactive({
data_frame = data.frame(hot_to_r(input$testdata))
levels = length(unique(data_frame$n))
data_frame1 = select(data_frame,c(n,mean,sd)) data_frame1$mean = as.numeric(data_frame$mean) data_frame1$sd = as.numeric(data_frame$sd) data_frame1$n = as.numeric(data_frame$n)
rnorm2 = function(n,mean,sd) { mean+ sd*scale(rnorm(n)) }
df = mapply(rnorm2,data_frame1[,1],data_frame1[,2],data_frame[,3])
if(levels > 1) { attributes(df) = list( names = names(df), row.names=1:max(data_frame$n), class = 'data.frame') colnames(df) = 1:ncol(df)
df2 =data.frame(values = unlist(df)) row.names(df2)= 1: nrow(df2)
data_frame2 = select(data_frame,c(Group,n)) data_frame2$Group = as.factor(data_frame2$Group) dataset1 = data_frame2 dataset1 = data.frame(ind = dataset1[rep(seq_len(nrow(dataset1)), dataset1$n) ,1 ]) row.names(dataset1) = 1:nrow(dataset1)
df2$ind = as.factor(dataset1$ind) } else
{ df = data.frame(df) df2 = data.frame(stack(df[1:ncol(df)])) #print(df2) }
data = df2
}) output$downloaddata <- downloadHandler( filename = function() { filetitle = paste("dataset") paste(filetitle, ".csv", sep = "") }, content = function(file) {
write.csv(datasetInput1(), file, row.names = FALSE) }
)
output$downloadPlot<- downloadHandler( filename = function() { paste("ANOVAplot", ".png", sep = "") }, content = function(file) { png(file)
if(input$ex == TRUE)
{data("ToothGrowth")
data = ToothGrowth
data$dose = factor(data$dose)}
else{
file1 = input$file if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
ds = data
ds = select(ds,input$variablex)
options(scipen = 999)
if(input$antype == "One-way")
{
mod = paste(input$variabley,"~")
mod = paste(mod,input$variablexd)
boxplot(as.formula(mod),data =ds,col = "red",ylab = input$variabley,xlab =input$variablexd,main = "One-way ANOVA Visualization")
} if(input$antype == "Two-way")
{ mod = paste(input$variabley,"~") mod = paste(mod,input$variablexd) mod = paste(mod,"+") mod = paste(mod,input$variablexd2) boxplot(as.formula(mod),data =ds,col = "red",xlab ="Treatments",ylab = input$variabley,main = "Two-way ANOVA Visualization ")
} if(input$antype == "Factorial") {
mod = paste(input$variabley,"~") mod = paste(mod,input$variablexd) mod = paste(mod,"*") mod = paste(mod,input$variablexd2) attach(ds) interaction.plot(get(input$variablexd),get(input$variablexd2),get(input$variabley),type ="b",col= c("red","blue"),main = "Interaction between Treatments",xlab = input$variablexd,ylab = input$variabley,trace.label = input$variablexd2)
}
dev.off() })
datasetInput2 <- reactive({ data("ToothGrowth") data = ToothGrowth data$dose = factor(data$dose) data = data }) output$downloaddata2 <- downloadHandler( filename = function() { filetitle = paste("Exampledataset") paste(filetitle, ".csv", sep = "") }, content = function(file) {
write.csv(datasetInput2(), file, row.names = FALSE) }
)
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