jml {MiscPsycho}R Documentation

Joint Maximum Likelihood Estimation for Rasch Item Parameters

Description

JML is used to estimate item parameters for the Rasch model.

Usage

jml(...)
## Default S3 method:
jml(dat, con = 1e-3, bias=FALSE, ...)
## S3 method for class 'formula':
jml(formula, data, na.action, subset, con = 1e-3, bias = FALSE, ...)

Arguments

formula an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted. The details of model specification are given under Details.
data an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which jml is called.
dat A data frame or matrix with item responses. Implemented only for the jml.default method.
na.action a function which indicates what should happen when the data contain NAs. Defaults to getOption("na.action").
subset an optional vector specifying a subset of observations to be used.
con Convergence criterion
bias Implements the correction for bias as described by Wright and Stone
... Not implemented

Details

Models for jml are specified symbolically. A typical model has the form ~item1 + item2 where the terms to the right of the ~ are the columns of the data matrix containing the binary item responses.

Value

A list with class "jml" containing the following components:

Estimate the value of Rasch item parameter (b-value)
Std.Error the standard error of the item parameter
Infit The Rasch infit statistic
Outfit The Rasch outfit statistic
Iterations the number of Newton-Raphson iterations used
model.frame the data matrix used for estimating item parameters. In JML estimation, individuals with all items correct and all items incorrect cannot be used in the calibration. Hence, they are dropped from the original data matrix provided by the data argument.

Author(s)

Harold Doran

Examples

set.seed(1234)
tmp <- data.frame(item1 = sample(c(0,1), 20, replace=TRUE), item2 = sample(c(0,1), 20, replace=TRUE),
item3 = sample(c(0,1), 20, replace=TRUE),item4 = sample(c(0,1), 20, replace=TRUE),item5 = sample(c(0,1), 20, replace=TRUE))

## Formula interface
fm1 <- jml(~ item1 + item2 + item3 + item4 + item5, data = tmp)
summary(fm1)
coef(fm1)
plot(fm1)

## Default interface
fm1 <- jml(tmp)
summary(fm1)

[Package MiscPsycho version 1.5 Index]