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normalityNew.R
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normalityNew.R
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# data = read.table("~/Documents/Studies/BiologicalVariation/Rcodes/data.txt",header = T, sep = "\t")
#
# data$Measurement = log(data$Measurement)
# dim(data)
#
# subject="Subject"
# analyte = "Measurement"
# replicate = "Replicate"
# time = "Time"
# gender="Gender"
#
# dataNew = outlier(data = data, analyte=analyte, subject=subject, replicate=replicate,
# time=time, gender=gender, decimal =3, outlierS1 = "subjetcs", outlierS2 = TRUE, outlierS3 = TRUE,
# showResult = showResult)
#
# dataNew$step1
# dataNew$step2
# dataNew$step3
#
# data = dataNew$dataWithoutOutliers
# dim(data2)
# head(data)
# subject="subject"
# analyte = "value"
# decimal=3
# test = "sw"
# transformation = TRUE
#
#
# showResult = "lnTransformed"
normalityNew <- function(data, subject, analyte, decimal, test = "sw", transformation = FALSE, showResult = "original"){
if(nrow(data) > 0){
library(nortest)
resultStep1 = NULL
resultStep2 = NULL
data <-data[order(data[, subject]),]
# analyteValue = data$value
# loganalytevalue = log(analyteValue)
# logdata = data
# logdata$value = loganalytevalue
if(showResult == "original"){
dat = "Original"
}
if(showResult == "lnTransformed"){
dat = "Log-transformed"
}
if(showResult == "transformBack"){
dat = "Transform back to original"
}
if(showResult == "cv"){
dat = "CV"
}
if(showResult == "mom"){
dat = "MoM"
}
if(showResult == "lnmom"){
dat = "lnMoM"
}
replicate = as.factor(data[,subject])
nreplicate = length(levels(replicate))
nameanalyte = analyte
# sw1 = tapply(analyteValue, replicate, shapiro.test)
#
#
splitData = split(data, data[,subject])
swList = list()
for(i in 1:length(splitData)){
tmp = splitData[[i]]
if(test == "sw"){
sw = shapiro.test(tmp[,analyte])
method = "Shapiro-Wilk"
}else{
sw = ad.test(tmp[,analyte])
method = "Anderson-Darling"
}
subj = paste0("Subject:",tmp[,subject][[1]])
stat = formatC(sw$statistic, digits = decimal, format = "f")
pValue = ifelse(sw$p.value<0.001, "<0.001", formatC(sw$p.value, digits = decimal, format = "f"))
res = ifelse(sw$p.value<0.05, "Non-normal", "Normal")
swList[[i]] = cbind.data.frame(subj, method, dat, stat, pValue, res)
}
swTestResult = do.call(rbind.data.frame, swList)
colnames(swTestResult) = c("Subject", "Method", "Data Type", "Statistic", "p value", "Result")
rownames(swTestResult) = NULL
meanval = tapply(data$value, replicate, mean)
if(test == "sw"){
sw2 = shapiro.test(meanval)
method = "Shapiro-Wilk"
}else{
sw2 = ad.test(meanval)
method = "Anderson-Darling"
}
stat = formatC(sw2$statistic, digits = decimal, format = "f")
pValue = ifelse(sw2$p.value<0.001, "<0.001", formatC(sw2$p.value, digits = decimal, format = "f"))
res = ifelse(sw2$p.value<0.05, "Non-normal", "Normal")
sw2TestResult = cbind.data.frame( method, dat, stat, pValue, res)
colnames(sw2TestResult) = c("Method", "Data Type", "Statistic", "p value", "Result")
rownames(sw2TestResult) = NULL
normalityResult = list(Step1 = swTestResult, Step2 = sw2TestResult)
return(normalityResult)
}
}