Drawing on the work of internationally acclaimed experts in the
field, Handbook of Item Response Theory, Volume Two: Statistical
Tools presents classical and modern statistical tools used in item
response theory (IRT). While IRT heavily depends on the use of
statistical tools for handling its models and applications,
systematic introductions and reviews that emphasize their relevance
to IRT are hardly found in the statistical literature. This second
volume in a three-volume set fills this void. Volume Two covers
common probability distributions, the issue of models with both
intentional and nuisance parameters, the use of information
criteria, methods for dealing with missing data, and model
identification issues. It also addresses recent developments in
parameter estimation and model fit and comparison, such as Bayesian
approaches, specifically Markov chain Monte Carlo (MCMC) methods.
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