Dear SAS Friends,
The good news is, the article was accepted. The bad news is one of the reviewers wants something (repeated measures ANOVA) and I don't know how to provide it.
Hopefully with the information I provide here you can tell me if I can even do it. I'd like to hope the reviewer has lost his/her mind, but I'm pretty sure I'm just not doing something correctly. 😉
Okay. I have a financial education course (treatment). I collected pretest scores (preknow) and posttest (postknow) scores. I have race (black/notblack), age (youngadult, adult, slightlyolderadult, midage, older), and education level (notgradhs hsgedordip somecollegeormore) as demographic variables. I have some other predictor variables, but we'll use these as an example and if I can run it I can figure it out (I hope, pray, think) from the information you all provide me here.
The reviewer wants to know who learned the most from the treatment/who learned more. When I googled repeated measures ANOVA, it led me to PROC GLM with some other nifty pieces. So, here's what I've got:
proc glm;
class black youngadult adult slightlyolderadult midage older notgradhs HSGEDorDip somecollegeormore;
model preknow postknow = black youngadult adult slightlyolderadult midage older notgradhs HSGEDorDip somecollegeormore black*notgradhs black*hsgedordip
black*somecollegeormore black*youngadult black*adult black*slightlyolderadult black*midage black*older /nouni;
repeated postknow;
lsmeans black youngadult adult slightlyolderadult midage older notgradhs HSGEDorDip somecollegeormore black*notgradhs black*hsgedordip
black*somecollegeormore black*youngadult black*adult black*slightlyolderadult black*midage black*older;
run;
Now, the good news is, the procedure runs. The bad news is I get crap.
For example:
somecollegeormore preknow LSMEAN postknow LSMEAN
0 Non-est Non-est
1 Non-est Non-est
black NotGradHS preknow LSMEAN postknow LSMEAN
0 0 Non-est Non-est
0 1 Non-est Non-est
1 0 Non-est Non-est
1 1 Non-est Non-est
and in the log
NOTE: H Matrix for postknow*youngadult has zero d.f.
NOTE: H Matrix for postknow*adult has zero d.f.
NOTE: H Matrix for postknow*slightlyolderadult has zero d.f.
NOTE: H Matrix for postknow*midage has zero d.f.
NOTE: H Matrix for postknow*older has zero d.f.
NOTE: H Matrix for postknow*black*NotGradHS has zero d.f.
NOTE: H Matrix for postknow*black*HSGEDorDip has zero d.f.
NOTE: H Matrix for postknow*black*somecollegeorm has zero d.f.
NOTE: H Matrix for postknow*black*youngadult has zero d.f.
NOTE: H Matrix for postknow*black*adult has zero d.f.
NOTE: H Matrix for postknow*black*slightlyoldera has zero d.f.
NOTE: H Matrix for postknow*black*midage has zero d.f.
NOTE: H Matrix for postknow*black*older has zero d.f.
NOTE: The Huynh-Feldt epsilon and the corresponding adjusted p-value have been enhanced to
include a correction based on Lecoutre (1991). Use the UEPSDEF=HF option on the REPEATED
statement to revert to the previous definition.
Thanks in advance for any help you can provide.
Kate
If I was right "(repeated measures ANOVA) " is called MIXED model.
You have two ways to do (repeated measures ANOVA) :
1) using proc glm + manova statement -- do some multiple variable analysis
Check proc glm's documentation ,there is an example about it .
Example 46.7: Repeated Measures Analysis of Variance
2) using MIXED Model. Check proc mixed, proc glmmix ..... @Steve @lvm can give you good advice.
P.S. I suggested you use Mixed model which have good ability to handle missing value.
If I was right "(repeated measures ANOVA) " is called MIXED model.
You have two ways to do (repeated measures ANOVA) :
1) using proc glm + manova statement -- do some multiple variable analysis
Check proc glm's documentation ,there is an example about it .
Example 46.7: Repeated Measures Analysis of Variance
2) using MIXED Model. Check proc mixed, proc glmmix ..... @Steve @lvm can give you good advice.
P.S. I suggested you use Mixed model which have good ability to handle missing value.
@Ksharp Thank you, I'll check out your suggestions!
I ended up using PROC MIXED...still no significant results, but I'm happy because I was right...ROFL.
Thanks for your help, @Ksharp
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 16. Read more here about why you should contribute and what is in it for you!
ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.
Find more tutorials on the SAS Users YouTube channel.