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  • Calculate confidence interval for multiple columns in a matrix (table) using R function CI_normal...

Calculate confidence interval for multiple columns in a matrix (table) using R function CI_normal and CI_tdist

  • Public
By EagleEye 535 days ago
#USAGE: CI_normal(matrix[,c(x:y)],97.5) - multiple column from a normal distribution #USAGE: CI_tdist(matrix[,c(x:y)],97.5) - multiple column from a t distribution #USAGE: CI_normal(matrix[,x],97.5) - single column from a normal distribution #USAGE: CI_tdist(matrix[,x],97.5) - single column from a t distribution #Created and updated by Santhilal Subhash on 2016/06/07 CI_normal <- function(li,stat) { cat(paste0("CI","\t","column","\t","Lower.limit","\t","Upper.limit","\n")) if(length(colnames(li))>1) { for(i in 1:length(colnames(li))) { sample <- colnames(li) error <- qnorm(stat/100)*sd(li[,i])/sqrt(length(li[,i])) left <- mean(li[,i])-error right <- mean(li[,i])+error cat(paste0(stat,"% norm dist","\t",sample[i],"\t",left,"\t",right,"\n")) } } else{ error <- qnorm(stat/100)*sd(li)/sqrt(length(li)) left <- mean(li)-error right <- mean(li)+error cat(paste0(stat,"% norm dist","\tNA","\t",left,"\t",right,"\n")) } } CI_tdist <- function(li,stat) { cat(paste0("CI","\t","column","\t","Lower.limit","\t","Upper.limit","\n")) if(length(colnames(li))>1) { for(i in 1:length(colnames(li))) { sample <- colnames(li) error <- qt(stat/100,df=length(li[,i])-1)*sd(li[,i])/sqrt(length(li[,i])) left <- mean(li[,i])-error right <- mean(li[,i])+error cat(paste0(stat,"% t-dist","\t",sample[i],"\t",left,"\t",right,"\n")) } } else{ error <- qt(stat/100,df=length(li)-1)*sd(li)/sqrt(length(li)) left <- mean(li)-error right <- mean(li)+error cat(paste0(stat,"% t-dist","\tNA","\t",left,"\t",right,"\n")) } }