rasch.prox: PROX Estimation Method for the Rasch Model

Description Usage Arguments Value References Examples

View source: R/rasch.prox.R

Description

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

Usage

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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

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#############################################################################
# EXAMPLE 1: PROX data.read
#############################################################################

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

Example output

- sirt 2.0-25 (2017-05-11 13:52:31)
         A1          A2          A3          A4          B1          B2 
-2.45493945 -1.47129174 -0.38516002  0.22673344 -1.29808410 -0.03481339 
         B3          B4          C1          C2          C3          C4 
-3.20730752 -1.09294800 -3.64572970 -1.29808410 -2.69987361 -1.44912858 

sirt documentation built on Feb. 18, 2020, 1:08 a.m.