The linear logistic test model (LLTM), a Rasch
model with linear constraints on the item parameters,
is described. Three methods of parameter estimation
are dealt with, giving special consideration
to the conditional maximum likelihood approach,
which provides a basis for the testing of structural
hypotheses regarding item difficulty. Standard
areas of application of the LLTM are surveyed, including
many references to empirical studies in
item analysis, item bias, and test construction; and
a novel type of application to
dynamic processes is presented. Finally, the linear
logistic model with relaxed assumptions (LLRA) for
measuring change is introduced as a special case of
an LLTM; it allows the characterization of individuals
in a multidimensional latent space and the
testing of hypotheses regarding effects of treatments.
Fischer, Gerhard H & Formann, Anton K. (1982). Some applications of logistic latent trait models with linear constraints on the parameters. Applied Psychological Measurement, 6, 397-416. doi:10.1177/014662168200600403
Fischer, Gerhard H.; Formann, Anton K..
Some applications of logistic latent trait models with linear constraints on the parameters.
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