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Lord, Frederic M. – 1984
There are currently three main approaches to parameter estimation in item response theory (IRT): (1) joint maximum likelihood, exemplified by LOGIST, yielding maximum likelihood estimates; (2) marginal maximum likelihood, exemplified by BILOG, yielding maximum likelihood estimates of item parameters (ability parameters can be estimated…
Descriptors: Bayesian Statistics, Comparative Analysis, Estimation (Mathematics), Latent Trait Theory
Engelen, R. J. H. – 1987
A short review of the different estimation procedures that have been used in association with the Rasch model is provided. These procedures include joint, conditional, and marginal maximum likelihood methods; Bayesian methods; minimum chi-square methods; and paired comparison estimation. A comparison of the marginal maximum likelihood estimation…
Descriptors: Bayesian Statistics, Chi Square, Comparative Analysis, Estimation (Mathematics)
Rabinowitz, Stanley N.; Pruzek, Robert – 1978
Despite advances in common factor analysis, a review of 89 studies published in four selected journals between 1963 and 1976 indicated that behavioral scientists preferred principal components analysis, followed by varimax or orthogonal rotation. Resultant row sums of squares of factor matrices from principal component analyses of real data sets…
Descriptors: Bayesian Statistics, Comparative Analysis, Educational Research, Factor Analysis
Park, Ok-choon; Tennyson, Robert D. – Contemporary Education Review, 1983
The theoretical rationales and procedures of five adaptive computer-based instruction models were reviewed: the mathematical model, the regression model, the Bayesian probabilistic model, the testing and branching model, and artificially intelligent instructional systems. Each model is assessed for contrast of methods and forms, identifiable…
Descriptors: Artificial Intelligence, Bayesian Statistics, Branching, Computer Assisted Instruction

And Others; Hambleton, Ronald K. – Review of Educational Research, 1978
Topics concerning latent trait theory are addressed: (1) dimensionality of latent space, local independence, and item characteristic curves; (2) models--equations, parameter estimation, testing assumptions, and goodness of fit, (3) applications test developments, item bias, tailored testing and equating; and (4) advantages over classical…
Descriptors: Ability, Bayesian Statistics, Goodness of Fit, Item Analysis