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ERIC Number: ED407428
Record Type: Non-Journal
Publication Date: 1997-Jan
Pages: 21
Abstractor: N/A
Reference Count: N/A
Regression Is a Univariate General Linear Model Subsuming Other Parametric Methods as Special Cases.
Vidal, Sherry
Although the concept of the general linear model (GLM) has existed since the 1960s, other univariate analyses such as the t-test and the analysis of variance models have remained popular. The GLM produces an equation that minimizes the mean differences of independent variables as they are related to a dependent variable. From a computer printout of a regression analysis, the researcher can obtain weights that apply to each variable and then construct this equation. Certain univariate analyses require some variables to be in a nominal scale versus an interval scale and then provide limited information about the data when compared with other data analytic tools. This paper explains how regression subsumes all univariate analyses and how regression can provide the researcher with a greater understanding of the data. A heuristic data set using fictitious data for eight boys and eight girls from a reading test is used to clarify this discussion. Correlation is the link that ties together all univariate analyses because regression represents the model that acts as an umbrella to all univariate analyses. An appendix presents a Statistical Package for the Social Sciences (SPSS) program to illustrate regression as a GLM. (Contains 1 figure, 6 tables, and 15 references.) (SLD)
Publication Type: Reports - Evaluative; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A