psychotools: guesspar – R documentation

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guesspar

Extract Guessing Parameters of Item Response Models

Description

A class and generic function for representing and extracting the so-called guessing parameters of a given item response model.

Usage

guesspar(object, ...)
  ## S3 method for class 'raschmodel'
guesspar(object, alias = TRUE, vcov = TRUE, ...)
  ## S3 method for class 'rsmodel'
guesspar(object, alias = TRUE, vcov = TRUE, ...)
  ## S3 method for class 'pcmodel'
guesspar(object, alias = TRUE, vcov = TRUE, ...)
  ## S3 method for class 'plmodel'
guesspar(object, alias = TRUE, logit = FALSE, vcov = TRUE, ...)
  ## S3 method for class 'gpcmodel'
guesspar(object, alias = TRUE, vcov = TRUE, ...)

Arguments

`object`	a fitted model object whose guessing parameters should be extracted.
`alias`	logical. If `TRUE` (the default), the aliased parameters are included in the return vector (and in the variance-covariance matrix if `vcov` = TRUE). If `FALSE`, these parameters are removed. For `raschmodel`s, `rsmodel`s, `pcmodel`s and `gpcmodel`s, where all guessing parameters are fixed to 0, this means that an empty numeric vector and an empty variance-covariace matrix is returned if `alias` is `FALSE`.
`logit`	logical. If a `plmodel` of `type` `"3PL"` or `"4PL"` model has been fit, the guessing parameters were estimated on the logit scale. If `logit = FALSE`, these estimates and the variance-covariance (if requested) are retransformed using the logistic function and the delta method.
`vcov`	logical. If `TRUE` (the default), the variance-covariance matrix of the guessing parameters is attached as attribute `vcov`.
`...`	further arguments which are currently not used.

Details

guesspar is both, a class to represent guessing parameters of item response models as well as a generic function. The generic function can be used to extract the guessing parameters of a given item response model.

For objects of class guesspar, several methods to standard generic functions exist: print, coef, vcov. coef and vcov can be used to extract the guessing parameters and their variance-covariance matrix without additional attributes.

Value

A named vector with guessing parameters of class guesspar and additional attributes model (the model name), alias (either TRUE or a named numeric vector with the aliased parameters not included in the return value), logit (indicating whether the estimates are on the logit scale or not), and vcov (the estimated and adjusted variance-covariance matrix).

Examples

if(requireNamespace("mirt")) {

o <- options(digits = 3)

## load simulated data
data("Sim3PL", package = "psychotools")

## fit 2PL to data simulated under the 3PL
twoplmod <- plmodel(Sim3PL$resp)

## extract the guessing parameters (all fixed at 0)
gp1 <- guesspar(twoplmod)

## fit 3PL to data simulated under the 3PL
threeplmod <- plmodel(Sim3PL$resp, type = "3PL")

## extract the guessing parameters
gp2 <- guesspar(threeplmod)

## extract the standard errors
sqrt(diag(vcov(gp2)))

## extract the guessing parameters on the logit scale
gp2_logit <- guesspar(threeplmod, logit = TRUE)

## along with the delta transformed standard errors
sqrt(diag(vcov(gp2_logit)))

options(digits = o$digits)
}

psychotools

Psychometric Modeling Infrastructure

v0.6-0

GPL-2 | GPL-3

Authors

Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Carolin Strobl [aut], Florian Wickelmaier [aut], Basil Komboz [aut], Julia Kopf [aut], Lennart Schneider [aut] (<https://orcid.org/0000-0003-4152-5308>), Rudolf Debelak [aut]

Initial release

2020-11-16