Help the Stat Consulting Group by
giving a gift
Loading
|
|
|
||||
|
Help the Stat Consulting Group by
giving a gift
| |||||
|
Loading
|
|||||
In chapter 10 Keppel shows how to perform a two way factorial anova on page 217. We use the anova command as shown below to get the analysis for the two way anova. The a*b term requests the interaction effect of a by b.
use http://www.ats.ucla.edu/stat/stata/examples/da/chap10, clear
anova errors a b a*b
Number of obs = 24 R-squared = 0.4590
Root MSE = 4.28174 Adj R-squared = 0.3087
Source | Partial SS df MS F Prob > F
-----------+----------------------------------------------------
Model | 280.00 5 56.00 3.05 0.0361
|
a | 112.00 2 56.00 3.05 0.0721
b | 24.00 1 24.00 1.31 0.2675
a*b | 144.00 2 72.00 3.93 0.0384
|
Residual | 330.00 18 18.3333333
-----------+----------------------------------------------------
Total | 610.00 23 26.5217391
On page 222, Keppel shows how to compute Omega Squared for the a*b effect. Stata does not have a built in command for computing this, however UCLA Academic Technology Services has created a command omega2 which will compute this for you. You can get this command by typing findit omega2 (see How can I use the findit command to search for programs and get additional help? for more information about using findit).
For a multifactor design, you supply the SS and df for the effect of interest. Since SSab was 144 and DFab was 2, we would type the following and that produces the omega squared value shown in Keppel.
omega2 a*b omega squared for a*b = 0.1961 fhat effect size = 0.4939
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