Hello, I have been trying to loop glimmix using the blog An easy way to run thousands of regressions in SAS - The DO Loop by @Rick_SAS . I believe I followed it step by step, but when I run the data I get different p values than if I wrote it out manually. In my case, I have 12 dependent variables and 31 predictors to test. I was wondering if anyone had any insight into why the looped version is giving me different results? when I checked the type 3 of fixed effects in the looped model phq9=gender, I got a pvalue of .96, but when I run it manually using the original data set perm.mental health, the pvalue is .61. Any help would be greatly appreciated! data perm.temp;
set perm.mentalhealth;
array var_list[12] trouble_sleeping hurting_yourself interest depressed little_energy appetite feeling_bad
concentrating moving_slowly PHQ9_SCORE Depression Anxiety;
do i=1 to dim(var_list);
VarName=vname(var_list(i));
put VarName=;
Outcome=vvalue(var_list[i]);
array categorical[22] gender age scalp_lesions postauricular erythema eyelid_involvement cheilitis flexural_erythema
xerosis neck_folds nipple_eczema keratosis palmar hand_eczema ichthyosis foot_eczema race education_final insurance alopecia pityriasis pain_severeB;
do j=1 to dim(categorical);
categorical_=vname(categorical(j));
put categorical_=;
CValue=vvalue(categorical[j]);
output;
end; end;
drop i j ;
format Depression Depressionn. Anxiety Anxietyy. interest interestt. depressed _depressedd. trouble_sleeping trouble_sleepingg.
little_energy little_energyy. appetite appetitee. feeling_bad feeling_badd. concentrating concentratingg.
moving_slowly moving_slowlyy. hurting_yourself hurting_yourselff. PHQ9_SCORE PHQ9_SCORE_. PHQ2_SCORE PHQ2_SCORE.
gender gender. race race. education_final education. insurance insurance. scalp_lesions scalp_lesionss. postauricular postauricularr. erythema erythemaa. eyelid_involvement eyelid_involvementt. cheilitis cheilitiss. flexural_erythema flexural_erythemaa. xerosis xerosiss. neck_folds neck_foldss. nipple_eczema nipple_eczemaa. keratosis keratosiss. palmar palmarr. hand_eczema hand_eczemaa. ichthyosis ichthyosiss. foot_eczema foot_eczemaa. age age_bin_. alopecia alopeciaa. pityriasis pityriasiss. pain_severeB painn. ;
run;
data perm.temp2;
set perm.mentalhealth;
array var_list[12] trouble_sleeping hurting_yourself interest depressed little_energy appetite feeling_bad
concentrating moving_slowly PHQ9_SCORE Depression Anxiety ;
do i=1 to dim(var_list);
VarName=vname(var_list(i));
put VarName=;
Outcome=vvalue(var_list[i]);
array npredictors[9] SCORAD EASI BSA ADSI POEM_SCORE dlqi_score FIVED_SCORE RL_SCORE flare;
do k=1 to dim(npredictors);
npredictors_=vname(npredictors(k));
Value=(npredictors[k]);
output;
end;end;
drop k;
format Depression Depressionn. Anxiety Anxietyy. interest interestt. depressed _depressedd. trouble_sleeping trouble_sleepingg.
little_energy little_energyy. appetite appetitee. feeling_bad feeling_badd. concentrating concentratingg.
moving_slowly moving_slowlyy. hurting_yourself hurting_yourselff. PHQ9_SCORE PHQ9_SCORE_. PHQ2_SCORE PHQ2_SCORE.
gender gender. race race. education_final education. insurance insurance. scalp_lesions scalp_lesionss. postauricular postauricularr. erythema erythemaa. eyelid_involvement eyelid_involvementt. cheilitis cheilitiss. flexural_erythema flexural_erythemaa. xerosis xerosiss. neck_folds neck_foldss. nipple_eczema nipple_eczemaa. keratosis keratosiss. palmar palmarr. hand_eczema hand_eczemaa. ichthyosis ichthyosiss. foot_eczema foot_eczemaa. age age_bin_. alopecia alopeciaa. pityriasis pityriasiss. pain_severeB painn. ;
run;
proc sort data=perm.temp;
by VarName categorical_;
run;
proc sort data=perm.temp2;
by VarName npredictors_;
run;
proc glimmix data=perm.temp method=laplace ;
by VarName categorical_;
class record_id_final CValue outcome ;
model outcome = CValue /link=cumlogit dist=multinomial solution;
random visit /subject=record_id_final;
run;
proc glimmix data=perm.temp2 method=laplace ;
by VarName npredictors_;
class record_id_final Value outcome ;
model outcome = Value /link=cumlogit dist=multinomial solution;
random visit /subject=record_id_final;
run; manual glimmix: proc glimmix data=perm.mentalhealth method=laplace order=internal ;
class record_id_final PHQ9_SCORE gender ;
model PHQ9_SCORE= gender /link=cumlogit dist=multinomial solution ;
random visit /subject=record_id_final;
run; log from do loop: results from testing the model phq9=gender: manual model: looped:
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