From the course: Advanced SAS Programming for R Users, Part 1
Unlock this course with a free trial
Join today to access over 22,400 courses taught by industry experts.
ANOVA and ANCOVA with the general linear model procedure - SAS Tutorial
From the course: Advanced SAS Programming for R Users, Part 1
ANOVA and ANCOVA with the general linear model procedure
- [Narrator] Now we're going to to move on from PROC REG and now into PROC GLM, which stands for general linear model. In this case, we're going to perform an ANOVA and also an analysis of covariance. We're moving away from PROC REG with just continuous variables and now we can use classification variables in PROC GLM. Here I'm going to continue working with the ameshousing dataset. To do an analysis of variance, I'm going to choose heating_qc, for quality control in that dataset. This has four levels: excellent, good, average, and fair. To tell SAS explicitly that's it a classification variable, I'm going to use the CLASS statement and specify the variable heating quality control. So the CLASS statement is identical to the as.factor function in R. It's going to create a column in the design matrix for each classification level. And as an option in parentheses, I'm going to specify the reference level. In this case, I'll set it equal to Fa for Fair. And again, that is case sensitive…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Contents
-
-
-
Linear regression with PROC REG3m 54s
-
Scoring new data sets2m 58s
-
Demo: Multiple linear regression6m 13s
-
Demo: Polynomial regression3m 4s
-
ANOVA and ANCOVA with the general linear model procedure6m 1s
-
Estimating linear combinations with the general linear model procedure3m 37s
-
Demo: Two-way ANOVA6m 15s
-
Demo: ANCOVA5m 58s
-
Affect selection with the GLMSELECT procedure5m 28s
-
Additional benefits of the GLMSELECT procedure3m 40s
-
Demo: Stepwise selection with PROC GLMSELECT8m 14s
-
Demo: Polynomial regression with the GLMSELECT procedure4m 9s
-
Logistic regression with the LOGISTIC procedure4m 38s
-
Counting concordant, discordant, and tied pairs in the logistic procedure2m 44s
-
Demo: Logistic regression7m 11s
-
Other generalized linear models with the GENMOD procedure3m 20s
-
Demo: GENMOD procedure9m 56s
-
Mixed models and the MIXED procedure5m 54s
-
Demo: Two-way mixed model6m 12s
-
Other procedures4m 4s
-