personfit

a computed model object of class
  <code>ExploratoryClass</code>, <code>ConfirmatoryClass</code>, or
  <code>MultipleGroupClass</code>

type of factor score estimation method. Can
  be expected a-posteriori (<code>"EAP"</code>), Bayes modal
  (<code>"MAP"</code>), weighted likelihood estimation
  (<code>"WLE"</code>), or maximum likelihood (<code>"ML"</code>)

method

<code>personfit</code> calculates the Zh values from Drasgow,
  Levine and Williams (1985) for unidimensional and
  multidimensional models. For Rasch models infit and
  outfit statistics are also produced. The returned object
  is a <code>data.frame</code> consisting either of the tabulated
  data or full data with the statistics appended to the
  last columns.

person

Analysis of dichotomous and polytomous response data using
        latent trait models under the Item Response Theory paradigm.
        Includes univariate and multivariate one-, two-, three-, and
        four-parameter logistic models, graded response models, rating
        scale graded response models, generalized partial credit
        models, nominal models, multiple choice models, and
        multivariate partially-compensatory models. These can be used
        in an exploratory or confirmatory manner with optional user
        defined linear constraints. Exploratory models can be estimated
        via quadrature or stochastic methods, a generalized
        confirmatory bi-factor analysis is included, and confirmatory
        models can be fit with a Metropolis-Hastings Robbins-Monro
        algorithm which can include polynomial or product constructed
        latent traits. Additionally, multiple group analysis may be
        performed for unidimensional or multidimensional item response
        models for detecting differential item functioning.

personfit: Person fit statistics

Description

Usage

Arguments

References

See Also

Examples