ltm (version 0.8-9)

fitted: Fitted Values for IRT model

Description

Computes the expected frequencies for vectors of response patterns.

Usage

## S3 method for class 'grm':
fitted(object, resp.patterns = NULL, 
    type = c("expected", "marginal-probabilities",
    "conditional-probabilities"), ...)

## S3 method for class 'ltm':
fitted(object, resp.patterns = NULL, 
    type = c("expected", "marginal-probabilities", 
    "conditional-probabilities"), ...)

## S3 method for class 'rasch':
fitted(object, resp.patterns = NULL, 
    type = c("expected", "marginal-probabilities", 
    "conditional-probabilities"), ...)

## S3 method for class 'tpm':
fitted(object, resp.patterns = NULL, 
    type = c("expected", "marginal-probabilities", 
    "conditional-probabilities"), ...)

Arguments

object

an object inheriting from either class grm, class ltm, class rasch, or class tpm.

resp.patterns

a matrix or a data.frame of response patterns with columns denoting the items; if NULL the expected frequencies are computed for the observed response patterns.

type

if type == "marginal-probabilities" the marginal probabilities for each response are computed; these are given by $\int { \prod_{i = 1}^p Pr(x_i = 1 | z)^{x_i} \times (1 - Pr(x_i = 1 | z))^{1 - x_i} }p(z) dz$, where $x_i$ de

...

additional arguments; currently none is used.

Value

• a numeric matrix or a list containing either the response patterns of interest with their expected frequencies or marginal probabilities, if type == "expected" || "marginal-probabilities" or the conditional probabilities for each response pattern and item, if type == "conditional-probabilities".

See Also

residuals.grm, residuals.ltm, residuals.rasch, residuals.tpm

Examples

fit <- grm(Science[c(1,3,4,7)])
fitted(fit, resp.patterns = matrix(1:4, nr = 4, nc = 4))

fit <- rasch(LSAT)
fitted(fit, type = "conditional-probabilities")