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rinugour
Fluorite | Level 6

 Explain what Proc glm does?

4 REPLIES 4
RW9
Diamond | Level 26 RW9
Diamond | Level 26

Posting a generic bolded instruction to us is not going to get you any useful information.

If you want to know what something does, RTFM!

https://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#glm_toc.htm

PaigeMiller
Diamond | Level 26

It fits general linear models, including (but not limited to) ANOVA and regression. Search the internet for general linear models, you will find a lot to read.

--
Paige Miller
Reeza
Super User

For these type of questions please check the documentation. The overview section of each proc explains what it does in general terms.

 

For example:

 

The GLM procedure uses the method of least squares to fit general linear models. Among the statistical methods available in PROC GLM are regression, analysis of variance, analysis of covariance, multivariate analysis of variance, and partial correlation.

PROC GLM analyzes data within the framework of general linear models. PROC GLM handles models relating one or several continuous dependent variables to one or several independent variables. The independent variables can be either classification variables, which divide the observations into discrete groups, or continuous variables. Thus, the GLM procedure can be used for many different analyses, including the following:

  • simple regression

  • multiple regression

  • analysis of variance (ANOVA), especially for unbalanced data

  • analysis of covariance

  • response surface models

  • weighted regression

  • polynomial regression

  • partial correlation

  • multivariate analysis of variance (MANOVA)

  • repeated measures analysis of variance

https://documentation.sas.com/?cdcId=pgmsascdc&cdcVersion=9.4_3.4&docsetId=statug&docsetTarget=statu...

 


@rinugour wrote:

 Explain what Proc glm does?


 

anjita
Fluorite | Level 6

Proc glm performs simple and multiple regressionanalysis of variance (ANOVA), analysis of covariance, multivariate analysis of variance and repeated measure analysis of variance.

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