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JC411911

Hello, I have the below code which is part of larger code that will stop running the rest of the program if there is a difference in the proc compare. It is working okay but I am curious if there is a way to rename the _type_ variable that is created for the comparison. Right now it list BASE and COMPARE which is great but for a user that isn't aware I would like to rename to the actual file names. Is this possible? %let diff_count = 0; /* Compare the TO_TAX and FROM_TAX BUWfiles */ PROC COMPARE BASE=WORK.TO_TAX_MODIFIED brief transpose COMPARE=WORK.FROM_TAX_MODIFIED OUT=COMPARISON OUTBASE OUTCOMP OUTDIF LISTOBS OUTNOEQUAL BRIEFSUMMARY; VAR member_number account_number payer_id ; title 'COMPARING FILE SENT AND RECEIVED FROM'; RUN; DATA _NULL_; SET COMPARISON END=eof; IF eof THEN CALL SYMPUT('diff_count', _N_); RUN;

YYK273

I'm currently working on testing the overall Proportional Hazards Assumption for my 5 multiple imputation datasets. My challenge lies in determining the overall p-value of the Supremum Test for Proportional Hazards Assumption. While the test only provides the Maximum Absolute Value and Pr > MaxAbsVal, I'm uncertain about how to derive the overall p-value from proc mianalyze. Could you kindly provide some guidance or insights on how to approach this issue? Any assistance or pointers you could offer would be greatly appreciated. Thank you very much for your time and assistance.

sunilbhardwaj

Testing Configuration Options for Job Flows in SAS Solution for IFRS 17

mitrakos

Hello everyone, I have survey data of approximately 5000 participants and I am currently looking to model the outcome of a dichotomized response variable to a predictor. Our question is if there is a trend of participants being more likely to be in the 1 level of the response variable as we move from 4 to 1 in the ordinal response predictor. The dichotomized response has levels 1 and 0 while the predictor is an ordinal survey response with levels 1 - "Yes - completely", 2 - "Yes - mostly", 3 - "Yes - somewhat", and 4 - "No". I am currently wondering how to structure my proc logistic code and also weighing the use of proc logistic vs. proc surveylogistic. I do not have survey weights, so it seems that proc surveylogistic would not be useful in comparison to proc logisitic. Here is my code so far: proc logistic data = import plots=all; class outcome q1 / param=ordinal; model outcome = q1; run; I chose ordinal for the param= statement however I am not sure about that, though changing the param= option does not change the model fit statistics. I will continue to read documentation about proc logistic to see what other options might suit, but if there are any suggestions please let me know. Thank you!

GeorgeTr

I am currently working on the analysis of animal behaviour (frequency and duration) in a 2 x 2 factorial design, on two days (d2 and d16). Behavioural frequencies were analysed with proc glimmix with a Poisson distribution and Log link function, and a multiplicative overdispersion parameter: proc glimmix data=behav; by Obs_Day; class Batch Sanitary Diet; model Fighting_Total_number = Batch Sanitary|Diet / dist=Poisson link=log; random _residual_; lsmeans Batch Sanitary|Diet / pdiff; run; Durations were analysed with proc glimmix, with a binomial distribution and logit link function, and a multiplicative overdispersion parameter: proc glimmix data = behav; NLoptions Maxiter = 2000; by Obs_Day; class Batch Sanitary Diet; model Fighting_Total_duration = Batch Sanitary|Diet / dist = binomial link = logit; random _residual_ ; lsmeans Batch Sanitary|Diet / pdiff; run; These are standard methods used by my department for such analyses. However, I was later told that because one treatment group had 0 incidences of a certain behaviour on d2, I cannot use proc glimmix. Is that so? If yes, what is the alternative? I would appreciate any help from the community.