Hi,   I am comparing the treatment difference and looking for the 95% CI by using Proc GLM. However it seems there are different CIs are produced from CLPARM and PDIFF.  Please see the code below:    proc glm data=xxx order=data;    class usubjid treatment;    model chg=treatment/solution clparm;    lsmeans treatment/stderr pdiff cl adjust=dunnett;   estimate 'Difference' treatment 1 -1; quit;   From option of CLPARM, I got below:   Estimate StdErr tValue Probt LowerCL UpperCL -2.03825641 3.79425842 -0.54 0.5924 -9.57081174 5.49429892   From option of PDIFF CL, I have, LowerCL Difference UpperCL -11.177164 -2.038256 7.100651   The difference of treatment are same from these two options, but CIs are different. Does anyone know what is the reason and which one we should use? Thanks very much,   Nancy ... View more

Hi,   I have a model y (disease status with 0 or 1) = sex + treatment, but there is no events for female at treatment B as below:     Disease Treatment A Treatment B Female 1 1 0   0 8 18 Male 1 9 5   0 87 86   Below code was used:   proc logistic data=xxx ; Class sex treatment ; model disease(event="1") = treatment sex sex*treatment; oddsratio treatmen/diff=ref; run;   I got warning message from SAS: WARNING: There is possibly a quasi-complete separation of data points. The maximum likelihood          estimate may not exist. WARNING: The LOGISTIC procedure continues in spite of the above warning. Results shown are based          on the last maximum likelihood iteration. Validity of the model fit is questionable.   Meanwhile SAS reported ORs (95% CI): Female: <0.001 (<0.001 >999.999) Male: 1.55(0.48,5.01)   I understand OR and CI are not making sense for Female, but how about OR and CI for Male, whether it is still making sense to interpret it? Any suggestion for this situation if I do want to keep both factors in the model?   Thank you very much for your help!   Nancy ... View more

Hi,   does anyone know how to interprate the fixed effects in Solutions when the intercept is canceled, such as Drug A, D,G and Gender F as below?   The GLM Procedure   Dependent Variable: Y   Parameter Estimate   StandardError t Value Pr > |t|Drug ADrug DDrug GGender FGender M 22.16666667 B 2.58800653 8.57 <.0001 39.06666667 B 2.58800653 15.10 <.0001 59.96666667 B 2.58800653 23.17 <.0001 4.26666667 B 2.58800653 1.65 0.1113 0.00000000 B . . .   Please see my code below:   proc glm data=DrugTest; class Drug gender; model Y = Drug GENDER/ noint solution; run;   Thank you so much! Nancy       ... View more