LSAT7

Data from Bock & Lieberman (1970); contains 5
  dichotomously scored items obtained from the Law School
  Admissions Test, section 7.

datasets

data

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.

LSAT7: Description of LSAT7 data

Description

Arguments

References