SAS/STAT User's Guide: GLM-VARCOMPThe SAS/STAT User's Guide, Version 6, Fourth Edition, Volume 1 and Volume 2, documents the procedures available with Release 6.06 of SAS/STAT software. Volume 1 contains the introductory chapters and documents the ACECLUS through FREQ procedures. Volume 2 documents the GLM through VARCOMP procedures. 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. |
Common terms and phrases
algorithm Analysis of Variance Censored Chi-Square class variables cluster computed confidence interval CORR covariance matrix created criterion data set contains DATA step default degrees of freedom dependent variable distribution effect eigenvalues ETHANOL example F statistic factor FREQ function independent input data set intercept label Least Squares Lemon LIFETEST Linear Models LOGISTIC MANOVA maximum MAXPULSE Mean Square method missing values MODEL statement multiple multivariate number of observations optimal OUTEST output data set OUTPUT statement parameter estimates plot predicted values principal component PRINCOMP Printed Output PROBIT PROC GLM PROC PRINQUAL proc print PROC REG PROC TRANSREG R-square random rank regression residual response variable REWEIGHT RSTPULSE RUNPULSE RUNTIME SAS data set SAS Language SAS System Source DF spline Spoon SSCP Standard Error statements produce Output statistics Stepwise Sum of Squares transformed variables Type TYPE=CORR univariate VARCLUS variable names vector WEIGHT statement XXXX XXXX XXXX XXXXXXX zero