Category: PROC GLIMMIX

The default technique is METHOD=RSPL, corresponding to maximizing the residual log pseudo-likelihood with an expansion about the current solutions of the best linear unbiased predictors of the random effects. In models for normal data with identity link, METHOD=RSPL and METHOD=RMPL are equivalent to restricted maximum likelihood estimation, and METHOD=MSPL and METHOD=MMPL are equivalent to maximum likelihood estimation.

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The following SAS Usage Note:

  http://support.sas.com/kb/37107 

  http://support.sas.com/kb/40724

 

provide information on testing covariance parameters when using PROC MIXED and PROC GLIMMIX.

 

proc glimmix data=asdf namelen=32;
where disaster_type /*age_desc*/ ne "";
class GROUPING_D_RISK_PT;

model &out
=
GROUPING_D_RISK_PT

/solution ddfm=kr dist=binomial link=logit s STDCOEF ;

lsmeans GROUPING_D_RISK_PT / ilink diff;

output out=gmxout residual=resid;
ods output
ParameterEstimates=kaz1
CovParms=uekawa1
nobs=jeana
ModelInfo=estes
dimensions=diminfo
ConvergenceStatus=concon
FitStatistics=FITSTAT
Diffs=DIF_RESULT
;
run;

Thanks J for this info:

Use dist=binary and link=logit for logistic regressino using PROG GLIMMIX.

The lSMEANS statemetn is available from this and it produces probability scores. Use ilink option:

lsmeans &group / ilink ;

For difference in the groups, you use the DIFF option on the LSMEANS statement. The results are also on the logit scale. If you use the OR option, you will get the odds ratios for the group effect --

lsmeans &group /diff or;

Unfortunately, the difference in the probability scale between the groups are not directly available in PROC GLIMMIX. The magnitude of the difference is easy to compute -- you use the results from the ILINK option output, which gives you the estimated probabilities in each group, and compute the difference by hand or by using a data step, however, the appropriate standard errors for these differences are not available in PROC GLIMMIX.

For logistic regression models in PROC GLIMMIX, you need to use dist=binary link=logit option on the MODEL statement (sorry I missed pointing this out in your program in my previous response). So please add these two options.

For logistic regression models, the estimations are all on the logit scale, so is the LSMEANS statement. To get the lsmeans on the original scale (the probability scale), you can use the ILINK option --

 

lsmeans &group / ilink ;

 

For difference in the groups, you use the DIFF option on the LSMEANS statement. The results are also on the logit scale. If you use the OR option, you will get the odds ratios for the group effect --

lsmeans &group /diff  or;

Unfortunately, the difference in the probability scale between the groups are not directly available in PROC GLIMMIX. The magnitude of the difference is easy to compute -- you use the results from the ILINK option output, which gives you the estimated probabilities in each group, and compute the difference by hand or by using a data step, however, the appropriate standard errors for these differences are not available in PROC GLIMMIX.

Thanks, JT.