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MULTIPLE REGRESSION AND PATH ANALYSIS

Gregory Carey, 1998 REGRESSION & path ANALYSIS - 1 MULTIPLE REGRESSION AND path ANALYSISI ntroductionPath ANALYSIS and MULTIPLE REGRESSION go hand in hand (almost). Also, it is easier to learnabout multivariate REGRESSION using path ANALYSIS than using algebra. We will start with anintuitive approach and later develop the algebraic the following SAS statements on the INTEREST data:LIBNAME carey '~carey/p7291dir';TITLE path ANALYSIS and Multivariate MULTIPLE REGRESSION ;PROC REG DATA= CORR;VAR lawyer architct educ vocab geometry;MODEL lawyer architct = educ vocab geometry / STB;MTEST / PRINT;This performs a MULTIPLE REGRESSION on two dependent variables, vocational interest in becoming alawyer (LAWYER) and vocational interest in becoming an (ARCHITCT). The independentvariables are education (EDUC) and two tests of cognitive ability, vocabulary (VOCAB) andgeometry (GEOMETRY). (Technically, it would be preferable to include other demographicssuch as gender and age in this ANALYSIS , but these variables are ignored here to keep matterssimple.)

Multivariate Multiple Regression & Path Analysis An astute person who examines the significance and values of the standardized beta weights and the correlations will quickly realize that interpretation through path analysis and interpretation of these weights give the same substantive conclusions. The chief advantage of

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