Mahmoud ★ Jordan, 20230311 13:21 (14 d 05:48 ago) Posting: # 23493 Views: 466 

Dear All In bioequivalence 2x2 (TR,TR) 3x3 ( TRR,RRT,RTR) and 2x4(TRTR,RTRT) for the statistical anaylsis based code SAS PROC MIXED; CLASSES SEQ SUBJ PER TRT; 1077 MODEL Y = SEQ PER TRT/ DDFM=SATTERTH; 1078 RANDOM TRT/TYPE=FA0(2) SUB=SUBJ G; 1079 REPEATED/GRP=TRT SUB=SUBJ; 1080 ESTIMATE 'T vs. R' TRT 1 1/CL ALPHA=0.1; run; By simulation study I found that MLE method better when number of fixed effects ≤ 4. REML method better when number of fixed effects > 4. Edit: Category and subject line changed; see also this post #1. [Helmut] 
PharmCat ★ Russia, 20230314 21:44 (10 d 21:26 ago) @ Mahmoud Posting: # 23501 Views: 324 

❝ MLE method better when number of fixed effects ≤ 4. ❝ REML method better when number of fixed effects > 4. Hi! Always use REML. Use ML only if you know exactly why. 
Mahmoud ★ Jordan, 20230315 09:35 (10 d 09:35 ago) @ PharmCat Posting: # 23503 Views: 319 

❝ ❝ MLE method better when number of fixed effects ≤ 4. ❝ ❝ REML method better when number of fixed effects > 4. ❝ ❝ Hi! Always use REML. Use ML only if you know exactly why. The greater the number of fixed effects, the greater the difference between REML and ML. 
PharmCat ★ Russia, 20230317 00:51 (8 d 18:18 ago) @ Mahmoud Posting: # 23505 Views: 266 

❝ The greater the number of fixed effects, the greater the difference between REML and ML. REML is an approach that produces unbiased estimators for some special cases and produces less biased estimates than ML in general. Some people say that REML is unbiased. It is like denominators N and N1 for variance if you have data from all general population  you can use ML, when you have a small part of population  you should use REML. If you have many independent observations (over 200 for example) then estimates will be nearly same. Some info. 