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grateful
Calcite | Level 5

Hi all, I am estimating predicted rates and am using GLIMMIX to estimate the probability of receiving an image (0/1) based on several dummies.  I am using GLIMMIX to support the random effect of the clinician and address the clusters of patients nested in clinicians.   The following syntax generates negative probabilities, which I suspect might be due to the distribution.  With LOGISTIC, I get probabilities btn  0 and 1, but I can't control for the clustering or random effects of the clinician. (in SAS 9.4)

 

My principal question is, how can I rescale the probabilities in GLIMMIX to be btn 0 & 1?

 

Thank you!

 

PROC GLIMMIX DATA=out.low_back_final_Spec_Gen4 METHOD=LAPLACE NOCLPRINT;
CLASS  image_rfr_npi;
MODEL   X_RAY_MRI_FLAG  = NPI_female Disable age AIDS ALCOHOL ANEMDEF ARTH BLDLOSS CHF CHRNLUNG COAG DEPRESS DM DMCX DRUG HTN HTNCX HYPOTHY LIVER LYMPH LYTES METS NEURO OBESE PARA PERIVASC PSYCH PULMCIRC RENLFAIL TUMOR ULCER VALVE WGHTLOSS Atlanta Bangor Boston Chattanooga Cleveland Dallas Des_Moines Elgin Greensboro Kingsport Madison Melrose_Park Milwaukee Morristown Nashville New_Brunswick New_Haven Omaha Orange_County Others Peoria Phoenix Pittsburgh Portland Raleigh San_Bernardino Seattle Springfield Sun_City Tampa Worcester

/  dist=binomial solution;
random intercept / type=vc subject=image_rfr_npi;
output out=LBP_GLIMMIX_PRED3 predicted=pred_value pred(ilink)=predprob;
COVTEST / WALD;
run;

1 ACCEPTED SOLUTION

Accepted Solutions
sld
Rhodochrosite | Level 12 sld
Rhodochrosite | Level 12

In the dataset LBP_GLIMMIX_PRED3,

 

pred_value contains predicted values for each observation on the link (logit) scale, which ranges negative to positive.

 

predprob contains predicted values for each observation on the inverse link (proportion) scale, which ranges 0 to 1

 

Are you looking at the correct variable? Does your predprob contain negative values?

 

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1 REPLY 1
sld
Rhodochrosite | Level 12 sld
Rhodochrosite | Level 12

In the dataset LBP_GLIMMIX_PRED3,

 

pred_value contains predicted values for each observation on the link (logit) scale, which ranges negative to positive.

 

predprob contains predicted values for each observation on the inverse link (proportion) scale, which ranges 0 to 1

 

Are you looking at the correct variable? Does your predprob contain negative values?

 

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