sirt (version 3.9-4)

rasch.prox: PROX Estimation Method for the Rasch Model

Description

This function estimates the Rasch model using the PROX algorithm (cited in Wright & Stone, 1999).

Usage

rasch.prox(dat, dat.resp=1 - is.na(dat), freq=rep(1,nrow(dat)),
    conv=0.001, maxiter=30, progress=FALSE)

Arguments

dat

An \(N \times I\) data frame of dichotomous response data. NAs are not allowed and must be indicated by zero entries in the response indicator matrix dat.resp.

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 dat.

conv

Convergence criterion for item parameters

maxiter

Maximum number of iterations

progress

Display progress?

Value

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

References

Wright, B., & Stone, W. (1999). Measurement Essentials. Wilmington: Wide Range.

Examples

# NOT RUN {
#############################################################################
# EXAMPLE 1: PROX data.read
#############################################################################

data(data.read)
mod <- sirt::rasch.prox( data.read )
mod$b       # item difficulties
# }

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