Hello, Exp details: 24 pens, 3 feed types (800, 400, 100), 8 replicates, RCBD The purpose is to evaluate a preference for feed type (800, 400, 100). To make the comparisons, three "treatments" were created (A = 800 vs 100, B= 800 vs 400, C =400 vs 100), the A,B, C treatments were used to allocate 2 of the 3 feeds to 1 pen in a RCBD. For 5 days, a known amount of feed was added to each feeder/pen, and after 24 h the feed was weighed back to determine the feed disappearance. Preference was defined as ((disappearance of ___ feed (800, 400, 100; respectively))/ Total feed disappearance (combined total of the 2 feeders/pen)*100). Giving the proportion of of each feed /pen/day. In the proposal (was proved to me...), the Statistical Analysis is suppose to be "...preference test as the fixed effect and replicate as the random effect. LSmean and means are to be separated using pdiff with Tukey's adjustment with pen as the EU." IMHO this somewhat lacking and not very descriptive. CODE: input PEN DIET Treatment Rep Feed pref1 pref2 pref3 pref4 pref5 1 1 3 1 800 68.7500 57.6471 67.8571 57.9545 78.9157 1 3 3 1 100 31.2500 42.3529 32.1429 42.0455 21.0843 2 1 1 1 800 79.7101 44.7368 44.4444 41.3043 48.3333 2 2 1 1 400 20.2899 55.2632 55.5556 58.6957 51.6667 3 2 2 1 400 100.0000 67.5676 85.1852 80.5825 56.0847 3 3 2 1 100 0.0000 32.4324 14.8148 19.4175 43.9153 4 1 1 2 800 92.5926 57.7465 65.5172 73.9130 59.0278 4 2 1 2 400 7.4074 42.2535 34.4828 26.0870 40.9722 .... ; Run; Proc Print; Run; %macro model_loop; %let yvar1 = pref1; %let yvar2 = pref2; %let yvar3 = pref3; %let yvar4 = pref4; %let yvar5 = pref5; %do i=1 %to 5 ; Proc Mixed data=Exp200 NOBOUND ASYCOV method=REML; Title "&&yvar&i"; class Pen Trt Rep Feed; model &&yvar&i = Feed/ddfm=Kenwardroger; random Rep / subject=Pen; lsmeans Feed/pdiff adjust=tukey; store out=work.glm&&yvar&i; run; proc plm restore=work.glm&&yvar&i; Title "&&yvar&i PLM"; lsmeans Feed/ pdiff lines adjust=tukey; run; %end; %mend model_loop; %model_loop; quit; The issue I'm having is a failure to converge . I have a feeling that it has to do with the specification of the subject. I guess I don't have a super specific question. I just don't feel like this is the correct way to analyze the data and looking for advice. Regards,
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