Hi to all!   I've faced with some strange formulation in some Clinical Study Protocol: "mixed ordered logistic regression" and I've tried to perform it using proc glimmix. Could you please help me with resolving difficulties in applying this?   My study is a crossover study, with 2 periods and 2 drugs. The study protocol says that I should include sequence, period and treatment as fixed effects and a repeated effect for patients within sequences to model and using a compound symmetry covariance structure. My endpoint ‘Ocular Discomfort’ is a scale and has following scores: 0 = no discomfort 1 = mild discomfort 2 = moderate discomfort 3 = severe discomfort 4 = very severe discomfort Also my endpoint was evaluated several times for visit the following time points: 0, 5, 10, 20 min.   I read that in the proc glimmix, I can specify a repeated structure by adding the _RESIDUAL_ keyword to the RANDOM statement. I wanted to use the following code:   proc glimmix data=t1 ;    class SUBJID sequence period drug timepoint;    model AVALC = sequence period drug/ CL dist=multinomial link=clogit solution ODDSRATIO;    random timepoint/ subject=SUBJID(sequence) residual type=cs;    estimate 'Trt vs. Control' drug 1 -1; run;   But it didn’t work and I got the following error:  "ERROR: R-side random effects are not supported for the multinomial distribution."   Now I have applied the model as follows, but I'm not sure if this satisfies the protocol requirements:   proc glimmix data=t1 method=laplace;    class SUBJID sequence period drug timepoint;    model AVALC = sequence period drug/ CL dist=multinomial link=clogit solution ODDSRATIO;    random timepoint/ subject=SUBJID(sequence) type=cs;    estimate 'Trt vs. Control' drug 1 -1; run;   I would be grateful for comments about the error using the _RESIDUAL_ and how can this be fixed? ... View more

Hi to All! Could you please help me with the choosing of a SAS procedure?   The study protocol states that: "The parameter 1 is ordered categorical variables. For these endpoints, the investigational product will be compared with the reference product using a mixed ordered logistic regression model. The model will include sequence, period and treatment as fixed effects and a repeated effect for patients within sequences, using a compound symmetry covariance structure. A 5% level of significance will be used to test for differences between the two treatments."   My endpoint is a scale and has values from 0 to 4. This study is a crossover study, with 2 periods and 2 drugs.   After some literature review and seach I've realized that the best choice would be proc glimmix in this case with the following syntax:   proc glimmix data=t1 method=laplace;    class SUBJID sequence period drug timepoint;    model AVALC = sequence period drug/ CL dist=multinomial link=clogit solution ODDSRATIO;    random timepoint/ subject=SUBJID(sequence) residual type=cs;    estimate 'Trt vs. Control' drug 1 -1; run;   What do you think? ... View more

Dear Sirs or madams, could you please help me with the NBRM analysis.   I have following data (the dataset in attchment): num_of_resp="Number of positive responses" offs="Offset" chis="Standartizied baseline val" site="Site" treatment="Treatment Arm"   And I have following description of the analysis in the SAP: NBRM is a negative binomial regression model for the number of events for all observation periods after the start of treatment. The Treatment Arm will be used as a fixed factor, the baseline will be used as covariates, the period as a factor with repetitions, and the interaction group “therapy arm× visit” will be included in the model. The model will use an unstructured covariance matrix [UN]. If there is no convergence, the 1st order autoregression matrix [AR (1)] and the composite symmetry covariance matrix [CS] will be used successively. If it is impossible to build a model or it is impossible to interpret a model with a period as a factor with repetitions, separate models will be constructed for each period after the start of therapy. For the supporting analysis, the same model will be built (or individual models by periods after the start of therapy) with the center as an additional fixed factor.   Could you please help with the code for the anlysis? Thanks in advanse, Best Regards, Andrey! ... View more

Hello everyone,   Could you please help me with following question? Some time ago the study was conducted and analyzed in SAS 9.3 and one of the analyses was provided using the following script:   ods output Tests3 = ANOVA ; proc glimmix data = cols1 ; class q1 y site usubjid; model chis12 = q1 y q1*y site chis / dist=negbin offset = offs ; random y / subject=usubjid type=ar(1) solution ; lsmeans q1*y/ diff cl ; run; At the moment the data with absolutely the same nature was collected and after running the SAS code on the new data,  we have the following results:       Could you please help to understand why there are no p-values for each effect? What is the best option for checking the data in this situation and what conclusions we can make here?   P.S. if you see any mistakes, please highlight it.   Thanks! ... View more

Hello all!   Could you please help me with the following question: I need to create the following table (this is example from CDISC😞     Following SAS code presented in the document:   PROC PHREG DATA=ADTTE; MODEL AVAL*CNSR (1 2 3) = TRTPN AGEGR1N SEXN / ALPHA=0.05; RUN;   I can't find event rate information at the output, could you please help me with it? Which SAS-code should be used for Event Rate evaluation at day 168 (I higlite it using red color in the table)?   Thanks in advance, Best Regards, Andrey ... View more

Dear Sirs and Madams!   I have faced with the following planned study:   The primary variable is the proportion of respondents. The hypothesis is non-inferiority. At the same time, stratification is planned for 2 factors, and this should be taken into account in the analysis of the primary variable.   Is it real to perform the procedure "the Farrington–Manning test extended to the Mantel–Haenszel type adjustment" in SAS? How to use Cochran-Mantel-Haenzel weights for the stratum weights in the calculation of the CI (this method corresponds to the expanded Farrington-Manning test (Farrington CP and Manning G 1990) for stratified designs with Cochran-Mantel-Haenzel weights)?   The data is attached.   Thanks in advance! Andrey   ... View more

Hello everybody!   I would be grateful if you could help me with calculations of sample size if I have following data:   1. Outcome is binary (Yes/No), main hypothesis is "non-inferiority"; 2. There are two planned analyses (60% - interim, 100% - final); 3. Non-inferiority margin = -20%; 4. True planed difference between reference and test drugs = -5% (reference effect=56% - Yes, test effect=51% - Yes); 5. Test one-tailed, alpha=5%, betta=80%.   I'm looking forward to hearing any suggestions or recommendations for solving this problem.   Best Regards, Anrey ... View more