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Posted 02-06-2020 04:39 PM
(868 views)
I'm using a mixed model with multiple random and fixed effects (REML) and continuous y and I would like to try using bootstrapping to get more accurate CI or SE values since even with transformation or BoxCox my y-data are not always normal. I don't find a proc to do this. Can someone help? I am quite familiar with JMP 14 and use SAS 7.154 a little bit. Thanks. Here's the code I'm starting with:
proc mixed data=phenoall;
class hyb n pd loc;
model nce=hyb n pd n*hyb pd*hyb n*pd;
random loc block(loc) pass(loc) loc*n loc*hyb;
lsmeans hyb / adjust=tukey;
run;
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Everything you ever wanted to know about bootstrapping in SAS
https://blogs.sas.com/content/iml/2018/12/12/essential-guide-bootstrapping-sas.html
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Paige Miller
Paige Miller
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Thanks. Just curious, does the bootstrapping give you better SE for the fixed effects or the random effects?