fscores

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

object

if <code>FALSE</code> (default) then a
  summary table with factor scores for each unique pattern
  is displayed. Otherwise the original data matrix is
  returned with the computed factor scores appended to the
  rightmost column

full.scores

rotation declaration to be used when
  estimating the factor scores. If <code>""</code> then the
  <code>object@rotate</code> default value is used (only
  applicable to <code>ExploratoryClass</code> objects)

rotate

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

method

number of quadratures to use per
  dimension

quadpts

verbose

Computes MAP, EAP, or ML factor scores with a
  multivariate normal prior distribution.

factor.scores

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,
        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.

fscores: Methods for Function fscores

Description

Usage

Arguments

Examples