BookmarkSubscribeRSS Feed
Yui_1122
Calcite | Level 5

Hello,

 

I'm encountering inconsistencies in results between Type 3 Tests of Fixed Effects and pairwise comparisons when using proc mixed.

 

My dataset consists of 5 subjects, each measured at 3 different time points. There are 15 observations in total.

 

I'm fitting a linear mixed-effects model to examine mean value differences among three groups. The Type 3 Test indicates a significant difference among at least one pair of groups (P-value = 0.0028), but none of the pairwise comparisons show significance (their p-values are 0.2096, 0.7895, and 0.8126). This discrepancy is puzzling to me.

 

For the variance-covariance structure, I've chosen the UN over CS and TOEP based on assumptions and AIC, but this inconsistency is specific to UN only and not observed with CS or TOEP.

 

Below is my SAS code. Any insights into this issue would be greatly appreciated!

 

proc mixed data=data plots=residualpanel;
class id group;
model outcome = group / s cl residual;
repeated group / subject=id type=UN r rcorr;
lsmeans group / cl diff;
run;

 

Thank you!!

4 REPLIES 4
Yui_1122
Calcite | Level 5

Hi Paige,

 

Thank you for your prompt reply!

 

However, my question differs from the one in the link you shared. In that case, the person observed both a significant Type 3 effect and confidence interval for one of the pairwise comparisons, which seems consistent. In my situation, I have only 3 groups, and I used LSMEANS for pairwise comparisons along with the Type 3 p-value. While the overall test result is significant, none of the 3 pairwise comparisons are. Additionally, my sample size is too small (n=15) to adjust for any interaction term. Moreover, my question is more focused on the discrepancies that arise from selecting different variance-covariance structures.

PaigeMiller
Diamond | Level 26

Overall tests use different logic and different math and answer different questions than the pairwise test. There is no reason to expect that the results will be consistent 100% of the time. Some of the time they will be consistent, other times they will not be consistent.

--
Paige Miller
Ksharp
Super User
That is two total different questions.
GROUP is significant means this variable can explain more/enough variance of Y variable in the model.

“lsmeans group” is checking the expected value/mean of different group value is different or not.
That is totally two differnt concept with the above.

SAS Innovate 2025: Call for Content

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 25. Read more here about why you should contribute and what is in it for you!

Submit your idea!

What is ANOVA?

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.

Discussion stats
  • 4 replies
  • 369 views
  • 4 likes
  • 3 in conversation