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Kreft, Ita G. G.; Kim, Kyung-Sung – 1990
A detailed comparison of four computer programs for analyzing hierarchical linear models is presented. The programs are: VARCL; HLM; ML2; and GENMOD. All are compiled, stand-alone, and specialized. All use maximum likelihood (ML) estimation for decomposition of the variance into different parts; and in all cases, computing the ML estimates…
Descriptors: Algorithms, Comparative Analysis, Computer Software, Computer Software Evaluation

Cudeck, Robert – Journal of Educational Statistics, 1991
Two algorithms that automatically select subsets of variables (PACE algorithm) and reference variables (Fabin estimators), respectively, used for the noniterative estimators are presented. The PACE algorithm is based on a nonsymmetric matrix sweep operator. A Monte Carlo experiment compares the relative performance of these estimators and others.…
Descriptors: Algorithms, Comparative Analysis, Equations (Mathematics), Estimation (Mathematics)

Wilson, Mark; Adams, Raymond J. – Journal of Educational Statistics, 1993
A marginal maximum likelihood estimation algorithm is presented for the ordered partition model of M. Wilson that does not require the set of available responses to be fully ordered. The model and its estimation algorithm are illustrated in a comparison of alternative scoring schemes for open-ended science items. (SLD)
Descriptors: Algorithms, Comparative Analysis, Elementary Secondary Education, Equations (Mathematics)
Chang, Shun-Wen; Twu, Bor-Yaun – 1998
This study investigated and compared the properties of five methods of item exposure control within the purview of estimating examinees' abilities in a computerized adaptive testing (CAT) context. Each of the exposure control algorithms was incorporated into the item selection procedure and the adaptive testing progressed based on the CAT design…
Descriptors: Adaptive Testing, Algorithms, Comparative Analysis, Computer Assisted Testing
Schnipke, Deborah L.; Reese, Lynda M. – 1997
Two-stage and multistage test designs provide a way of roughly adapting item difficulty to test-taker ability. All test takers take a parallel stage-one test, and, based on their scores, they are routed to tests of different difficulty levels in subsequent stages. These designs provide some of the benefits of standard computerized adaptive testing…
Descriptors: Ability, Adaptive Testing, Algorithms, Comparative Analysis
Skaggs, Gary; Stevenson, Jose – 1986
This study assesses the accuracy of ASCAL, a microcomputer-based program for estimating item parameters for the three-parameter logistic model in item response theory. Item responses are generated from a three-parameter model, and item parameter estimates from ASCAL are compared to the generating item parameters and to estimates produced by…
Descriptors: Algorithms, Comparative Analysis, Computer Software, Estimation (Mathematics)
Shermis, Mark D.; And Others – 1992
The reliability of four branching algorithms commonly used in computer adaptive testing (CAT) was examined. These algorithms were: (1) maximum likelihood (MLE); (2) Bayesian; (3) modal Bayesian; and (4) crossover. Sixty-eight undergraduate college students were randomly assigned to one of the four conditions using the HyperCard-based CAT program,…
Descriptors: Adaptive Testing, Algorithms, Bayesian Statistics, Comparative Analysis