Response Pattern in a Binary Matrix
Computes different statistics of the response pattern in a binary matrix.
md.pattern.sirt(dat)
dat |
A binary data matrix |
A list with following entries:
dat |
Original dataset |
dat.resp1 |
Indices for responses of 1's |
dat.resp0 |
Indices for responses of 0's |
resp_patt |
Vector of response patterns |
unique_resp_patt |
Unique response patterns |
unique_resp_patt_freq |
Frequencies of unique response patterns |
unique_resp_patt_firstobs |
First observation in original dataset
|
freq1 |
Frequencies of 1's |
freq0 |
Frequencies of 0's |
dat.ordered |
Dataset according to response patterns |
See also the md.pattern function in the mice package.
############################################################################# # EXAMPLE 1: Response patterns ############################################################################# set.seed(7654) N <- 21 # number of rows I <- 4 # number of columns dat <- matrix( 1*( stats::runif(N*I) > .3 ), N, I ) res <- sirt::md.pattern.sirt(dat) # plot of response patterns res$dat.ordered image( z=t(res$dat.ordered), y=1:N, x=1:I, xlab="Items", ylab="Persons") # 0's are yellow and 1's are red ############################################################################# # EXAMPLE 2: Item response patterns for dataset data.read ############################################################################# data(data.read) dat <- data.read ; N <- nrow(dat) ; I <- ncol(dat) # order items according to p values dat <- dat[, order(colMeans(dat, na.rm=TRUE )) ] # analyzing response pattern res <- sirt::md.pattern.sirt(dat) res$dat.ordered image( z=t(res$dat.ordered), y=1:N, x=1:I, xlab="Items", ylab="Persons")
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