topic RANDOM statements in PROC GLIMMIX for cluster, strata, and weight in a longitudinal mixed effects in Statistical Procedures

RANDOM statements in PROC GLIMMIX for cluster, strata, and weight in a longitudinal mixed effects

kai_cody — Tue, 29 Sep 2020 16:32:40 GMT

Hi all,

I am using PROC GLIMMIX perform a longitudinal binary mixed effects model on complex survey data. I am unsure what I need to do with the RANDOM statements to account for everything. Completely new to mixed effects models, sorry!

First, I have cluster (PSU - 2 levels), strata (99 levels), and final weights for each ID for each of four timepoints (Wave 1, 2, 3, 4 -- "repeated measures"). Here is an example of my dataset structure for the first two ID participants:

ID WAVE PSU STRATA WEIGHT STROKE

1 1 2 94 34724.3 No

1 2 2 94 48284.2 No

1 3 2 94 52843.3 No

1 4 2 94 48848.4 Yes

2 1 1 55 553.6 No

2 2 1 55 364.1 No

2 3 1 55 152.4 No

2 4 1 55 868.0 No

How should my PROC GLIMMIX code look? Here is what I have below, but does this account correctly for everything? Should I account for weighting in a separate WEIGHT statement?

proc glimmix data=DATASET method=quad;
class ID WAVE PSU STRATA V1 V2;
model STROKE = V1 V2 WAVE / dist=bin link=logit solution;
random PSU(STRATA) / subject=ID weight=WEIGHT;
random WAVE / subject=ID weight=WEIGHT;
run;

Thank you very much!

Re: RANDOM statements in PROC GLIMMIX for cluster, strata, and weight in a longitudinal mixed effect

gcjfernandez — Sat, 03 Oct 2020 18:46:15 GMT

Please refer the following SAS Global Forum paper; https://www.sas.com/content/dam/SAS/support/en/sas-global-forum-proceedings/2020/4937-2020.pdf

Re: RANDOM statements in PROC GLIMMIX for cluster, strata, and weight in a longitudinal mixed effect

kai_cody — Wed, 07 Oct 2020 16:49:58 GMT

This is what I ended up with. I think it is correct, but now SAS is saying there is insufficient memory to run this, even after I adjusted MEMSIZE. But anyways, maybe this is helpful:

proc sort data=PATH_DATA;
by ID WAVE; run;

proc glimmix data=PATH_DATA;
class GENDER2 RACE2 HISPANIC2 AGE2 ALCOHOL CIG DIABETE EDUC1 EMPLOY1 DUAL VARPSU VARSTRAT INCOME MARITAL1 BMI INSURANCE1 REGION1;
model STROKE = GENDER2 RACE2 HISPANIC2 WAVE AGE2 ALCOHOL CIG DIABETE EDUC1 EMPLOY1 DUAL INCOME MARITAL1 BMI INSURANCE1 REGION1/ link=logit solution oddsratio;
random WAVE intercept / subject=ID;
random VARPSU(VARSTRAT);
weight WEIGHT;
run;