#################################################################################
# Function to compute number and proportion of missing data for each item
#################################################################################
miss = function(x, order = FALSE,...){
#Convert blanks ("") to NA's
x[x == ""] = NA
# x is a data frame with an ID variable column of raw responses
# assume that missing can be detected; so no blank spaces as levels
missingness = apply(x[ , 1:length(x)], MARGIN = 2, function(x) sum(is.na(x)))
# store data into a single data frame
missData = data.frame(
item = names(missingness),
numMiss = missingness,
propMiss = missingness/nrow(x)
)
# when option=T, this inner function will be applied to data frame
if(order == TRUE){
missData = missData[order(missData$numMiss), ]
}
return(missData[,-1])
}
#item.response.data <- read.csv("C:/Users/Kory/Desktop/R group/code a thon/math.csv", na.strings="")
#item.response.data1 <- item.response.data[,-1]
#miss(item.response.data, order=F)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.