|
|
|
||||
|
|
|||||
10. Two Way Analysis of Variance, Page 217 of Keppel
Example 10a..SPSS MANOVA
Example 10b. SPSS GLM
Example 10c. SAS PROC GLM
10. Two Way Analysis of Variance, Page 217 of Keppel
Page 217 of Keppel illustrates how to perform a two way Analysis of Variance. This example compares three treatments (control, drug X, and drug Y) that represent factor a at two different durations (1 hour, 24 hours) representing factor. Four subjects were randomly assigned to each of these conditions and their performance (in terms of errors) was measured. The data for this experiment is shown below.
| control a=1 |
drug x a=2 |
drug y a=3 |
|
| 1 hour b=1 |
1 4 0 7 |
13 5 7 15 |
9 16 18 3 |
| 24 hours b=2 |
15 6 10 13 |
6 18 9 15 |
14 7 6 13 |
This can be analyzed using SPSS MANOVA, SPSS GLM, or SAS GLM. All of these examples use the CHAP10 (SPSS, SAS) data file. The following examples illustrate how to perform a two way factorial Analysis of Variance using this data.
Example 10a. SPSS MANOVA
MANOVA errors BY a(1,3) b(1,2).
The manova command for a two way ANOVA is much like the command for the one way ANOVA, except that two factors are supplied after the by keyword. The BY a(1,3) b(1,2) portion indicates there are two independent variables and a has 3 levels, and b has 2 levels. By default, manova will perform a factorial ANOVA.
Example 10b. SPSS GLM
GLM errors BY a b.
Example 10c. SAS PROC GLM
PROC GLM DATA=chap10; CLASS a b ; MODEL errors = a b a*b; MEANS a b a*b ; RUN;
Summary
Under construction.
UCLA Researchers are invited to our Statistical Consulting Services
We recommend others to our list of Other Resources for Statistical Computing Help
These pages are Copyrighted (c) by UCLA Academic Technology Services