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ERIC Number: ED340731
Record Type: Non-Journal
Publication Date: 1990-Feb
Pages: 112
Abstractor: N/A
Reference Count: N/A
Comparing Four Different Statistical Packages for Hierarchical Linear Regression: GENMOD, HLM, ML2, and VARCL.
Kreft, Ita G. G.; And Others
An overview is given of the available statistical theory and software for analyzing hierarchically nested data. Programs are evaluated, and general techniques are proposed to analyze data from several domains. This research is part of a larger project to evaluate elementary education in the Netherlands. The models discussed are the random coefficient models, the hierarchical mixed linear models, and the multilevel linear models. The abstract characteristics of the three classes of models and the systematic treatment of random and non-random parts of each class are described. Transformation of the models and the likelihood function are considered. The following four computer programs, using various types of algorithms, are discussed: (1) GENMOD; (2) HLM; (3) ML2; and (4) VARCL. Each is compared for design, implementation, performance and results, and ease of use. To overcome some of the disadvantages of these techniques, a new program, MULTIPATH, is proposed for a more general approach to the analysis of data from different domains. Thirteen data tables and a 61-item list of references are included. (SLD)
CSE Dissemination Office, UCLA Graduate School of Education, 405 Hilgard Avenue, Los Angeles, CA 90024-1521.
Publication Type: Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: Institute for Educational Research in the Netherlands (SVO), The Hague.
Authoring Institution: Center for Research on Evaluation, Standards, and Student Testing, Los Angeles, CA.
Identifiers - Location: Netherlands