library(shiny)
library(lme4)

shinyServer(function(input, output) {

  #Return the requested data

   datasetInput <- reactive({

    # input$file1 will be NULL initially. After the user selects
    # and uploads a file, it will be a data frame with 'name',
    # 'size', 'type', and 'datapath' columns. The 'datapath'
    # column will contain the local filenames where the data can
    # be found.

    inFile <- input$file1

    if (is.null(inFile))
      return(NULL)

    read.csv(inFile$datapath, header=input$header, sep=input$sep,
				 quote=input$quote)

   })

  # Show the first "n" observations
  output$table <- renderTable({
    head(datasetInput(), n = 20)
  })

  # Generate a summary of the dataset
  output$summary <- renderPrint({
    dataset <- datasetInput()
    summary(dataset)
  })

  # Select a response variable

  output$varselect <- renderUI({
    cols <- names(datasetInput())
    selectInput("variable", "Select a response variable:",choices=cols, selected=cols)

  })

  # Select a random effect variable
  output$varselect2 <- renderUI({
    cols <- names(datasetInput())
    selectInput("variable2", "Select a random effect variable:",choices=cols, selected=cols)

  })

   # Select time variable
  output$varselect3 <- renderUI({
    cols <- names(datasetInput())
    checkboxGroupInput("variable3", "Depends on which variable:",choices=cols)
  })

  # Select other factor variable
  output$varselect4<- renderUI({
    cols <- names(datasetInput())
    checkboxGroupInput("variable4", "Group factor variable:",choices=cols)
  })

  # Generate a analysis of the dataset(REML=FALSE)
  output$analysis<- renderPrint({
		dataset<-datasetInput()
	datafile<-dataset[,c(input$variable,input$variable2,input							$variable3,input$variable4),drop=FALSE]
	datafile[,4]<-as.factor(datafile[,4])
	col<-dim(datafile)[2]
	p<-length(levels(datafile[,4]))+2
	name<-names(datafile)
	test<-paste(name[1],"~","1+",name[4],":",name[3])
	form<-as.formula(test)
	fit<-lm(form,data=datafile)
	AIC<-as.numeric(logLik(fit))*(-2)+2*p
	result<-list(summary(fit),AIC)
	names(result)<-c("Summary","AIC")
	result
	})

  # Generate a analysis of the dataset(REML=FALSE)
  output$analysis2<- renderPrint({
		dataset<-datasetInput()
	datafile<-dataset[,c(input$variable,input$variable2,input							$variable3,input$variable4),drop=FALSE]
	datafile[,4]<-as.factor(datafile[,4])
	col<-dim(datafile)[2]
	name<-names(datafile)
	test<-paste(name[1],"~","1+(1|",name[2],")","+",name[4],":",name[3])
	form<-as.formula(test)
	fit<-lmer(form,data=datafile,REML=FALSE)
	summary(fit)
	})

  # Generate a analysis of the dataset(REML=FALSE)
  output$analysis3<- renderPrint({
		dataset<-datasetInput()
	datafile<-dataset[,c(input$variable,input$variable2,input							$variable3,input$variable4),drop=FALSE]
	datafile[,4]<-as.factor(datafile[,4])
	col<-dim(datafile)[2]
	name<-names(datafile)
	test<-paste(name[1],"~","1+(1+",name[3],"|",name[2],")","+",name[4],":",name[3])
	form<-as.formula(test)
	fit<-lmer(form,data=datafile,REML=FALSE)
	summary(fit)
  })
})