topic Glimmix output: same factor got different significance value from "Solutions for Fixed Effects" and "Type III Tests of Fixed Effects" in Statistical Procedures

Glimmix output: same factor got different significance value from "Solutions for Fixed Effects" and "Type III Tests of Fixed Effects"

lidove — Tue, 30 Aug 2011 04:03:41 GMT

Dear All,

I am a beginner of SAS. I used glimmix procedure to model how a binary response variable was affected by several interested factors. The output gave inconsistent results of the significance test of one factor, "gender", from the "Solutions for Fixed Effects" and "Type III Tests of Fixed Effects" (please see the attached results). Could anybody tell me: 1) what's the reason for my results? Is it due to the nature of my dataset which is unbalanced? 2) And under this situation, how do I intepret my results? which result should I belive, "Solutions for Fixed Effects" or "Type III Tests of Fixed Effects"?

Thanks for the help.

Solutions for Fixed Effects

Effect Nestlingsex Estimate Standard Error DF t P

Intercept 2.7637 0.3415 446.8 8.09 <0.0001

……

Gender female -0.8945 0.3448 9237 -2.59 0.0095

Gender male 0

……

Type III Tests of Fixed Effects

Effect Num DF Den DF F Value Pr > F

……

Gender 1 9237 0.04 0.8491

……

Glimmix output: same factor got different significance value from "Solutions for Fixed Effects" and "Type III Tests of Fixed Effects"

SteveDenham — Tue, 30 Aug 2011 11:22:01 GMT

That seems odd. Can you share your PROC GLIMMIX code, and the entirety of your Type3 output? I have a hunch you have some interactions with gender that might be significant, but I'm really just guessing.

Steve Denham

Glimmix output: same factor got different significance value from "Solutions for Fixed Effects" and "Type III Tests of Fixed Effects"

lidove — Tue, 30 Aug 2011 13:31:44 GMT

Thank you so much, Steve. The work is to examine what kinds of factors would affect whether a nestling bird would be fed during each feeding event. The SAS code and type 3 output are as follows:

proc glimmixdata = sasuser.EACHALLOCATION ;

class adult nestling gender nest position begging CB No_feeding_event;

title GLIMMIX Each Feeding preferenc;

model F_N(event='1') = adult gender position begging Tsize CB adult*gender adult*position adult*begging adult*Tsize adult*CB gender*position gender*begging gender*CB gender*Tsize position*begging position*CB position*Tsize begging*CB begging*Tsize Tsize*CB NO_begging_nestlings /solution ddfm=kr link = logit dist = binomial ;

random intercept no_feeding_event / subject=nest;

run;

Type III Tests of Fixed Effects
Effect	Num DF	Den DF	F Value	Pr > F
Adult	2	6925	1.69	0.1845
Gender	1	9237	0.04	0.8491
Position	1	9237	844.43	<.0001
Begging	1	9237	338.44	<.0001
Tsize	1	9237	2.06	0.1516
CB	1	32.61	0.22	0.6394
Adult*Gender	2	9237	3.66	0.0259
Adult*Position	2	9237	0.17	0.8460
Adult*Begging	2	9237	4.29	0.0138
Tsize*Adult	2	9237	4.48	0.0114
Adult*CB	1	7807	0.18	0.6747
Gender*Position	1	9237	2.61	0.1060
Gender*Begging	1	9237	2.12	0.1454
Gender*CB	1	5463	1.47	0.2253
Tsize*Gender	1	9237	0.01	0.9216
Position*Begging	1	9237	9.41	0.0022
Position*CB	1	9237	1.81	0.1785
Tsize*Position	1	9237	1.43	0.2313
Begging*CB	1	9237	2.19	0.1390
Tsize*Begging	1	9237	0.32	0.5746
Tsize*CB	1	9237	0.23	0.6333
No_begging_nestlings	1	2185	45.46	<.0001

Glimmix output: same factor got different significance value from "Solutions for Fixed Effects" and "Type III Tests of Fixed Effects"

SteveDenham — Wed, 31 Aug 2011 11:37:45 GMT

It doesn't depend on the significance of the interaction--the mere inclusion of the interaction in the model will lead to differences between the solution values and the F test values. I found this to be true even with balanced data. Thus, I would trust the F test values, for a couple of reasons. It considers the effect after "factoring out" all the other effects--it is meant to be an orthogonal test to all the other tests. The theory part of my brain seems to be non-functional this morning, but I know this difference should be apparent to me in the face of including interactions. The agreement will probably get worse with imbalance, especially with a Kenward-Rogers adjustment.

Steve Denham