White Papers

Comparison of Features and Applications of Four Linear Models Procedures

Category: Data Management, Software and Web Development

Tags: data

Overview Development of SAS linear models procedures over the past several years has led to a number of easily accessible methodological statistical advances for experimental data analysis. The original linear models program, GLM, was a fixed model procedure for analysis of normally distributed data with homogeneous variances. The GENMOD procedure extended the fixed linear model analysis to a number of non-normal distributions. With the use of GEE, GENMOD was able to address correlated repeated measures data. The MIXED procedure permitted the user to model both fixed and random effects for normally distributed variables. Because modeling of random effects permits multiple residual error terms, it is frequently possible to model heterogeneous residual variances.

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Publisher: SAS Institute
File Format: PDF
Date Published: May 29, 2009
Format: White Papers
Topics: Programming Languages, Data Mining - Analysis

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