PROX Estimation Method for the Rasch Model
This function estimates the Rasch model using the PROX algorithm (cited in Wright & Stone, 1999).
rasch.prox(dat, dat.resp=1 - is.na(dat), freq=rep(1,nrow(dat)),
conv=0.001, maxiter=30, progress=FALSE)dat |
An N \times I data frame of dichotomous response data. |
dat.resp |
An N \times I indicator data frame of nonmissing item responses. |
freq |
A vector of frequencies (or weights) of all rows in data frame |
conv |
Convergence criterion for item parameters |
maxiter |
Maximum number of iterations |
progress |
Display progress? |
A list with following entries
b |
Estimated item difficulties |
theta |
Estimated person abilities |
iter |
Number of iterations |
sigma.i |
Item standard deviations |
sigma.n |
Person standard deviations |
Wright, B., & Stone, W. (1999). Measurement Essentials. Wilmington: Wide Range.
############################################################################# # EXAMPLE 1: PROX data.read ############################################################################# data(data.read) mod <- sirt::rasch.prox( data.read ) mod$b # item difficulties
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