hauselin

#function to compute R2s in logistic regression
logisticR2s <- function(logisticModel) {
    modelDeviance <- logisticModel$deviance 
    nullDeviance <- logisticModel$null.deviance
    n <- length(logisticModel$fitted.values)
    
    R2HosmerLemeshow <- 1 - modelDeviance / nullDeviance
    R2CoxSnell <- 1 - exp((modelDeviance - nullDeviance) / n) 
    R2Nagelkerke <- R2CoxSnell / (1 - exp( - (nullDeviance / n)))
    

hauselin

data <- structure(list(id = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
                                2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 
                                5L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 
                                8L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 
                                11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 14L, 
                                14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 
                                16L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L, 19L, 19L, 
                                19L, 19L, 19L, 20L, 20L, 20L, 20L, 20L, 21L, 21L, 21L, 21L, 21L, 
                                22L, 22L, 22L, 22L, 22L, 23L, 23L, 23L, 23L, 23L, 24L, 24L, 24L, 
                                24L, 24L, 25L, 25L, 25L, 25L, 25L, 26L, 26L, 26L, 26L, 26L, 27L, 

hauselin

#for tutorial, see https://rpubs.com/hauselin/outliersDetect
#clean vector using Z-score cut-off method; return a vector with outliers = replace (default is NA)
outliersZ <- function(data, zCutOff = 1.96, replace = NA, values = FALSE, digits = 2) {
    #compute standard deviation (sample version n = n [not n-1])
    stdev <- sqrt(sum((data - mean(data, na.rm = T))^2, na.rm = T) / sum(!is.na(data)))
    #compute absolute Z values for each value
    absZ <- abs(data - mean(data, na.rm = T)) / stdev
    #subset data that has absZ greater than the zCutOff and replace them with replace
    #can also replace with other values (such as max/mean of data)
    data[absZ > zCutOff] <- replace 

hauselin

  ############################################################################
  #                                                                          #
  #  Excluding participants who participated in previous studies             #
  #  By Arnoud Plantinga, based on Gabriele Paolacci's Excel solution        #
  #                                                                          #
  #  Instructions (Note: edit only the non-indented lines):                  #
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