Hi Chuie, I would reshape your current wide data to long data as such   school teleclinic time count A Yes 0 50 A Yes 1 60 A Yes 2 13 A Yes 3 30 B No 0 151 B No 1 122 B No 2 155 B No 3 16   where time=0=pre, ..., time=3=after ED count(2016)  and  model by Poisson Regression. Your outcome variable will be count. The independent variables will be teleclinic, time and teleclinic*time and specify them as categorical variables. The interaction term will test if the effect of teleclinic on your outcome variable differs at each time point. If overdispersion exists, you will have to try to model by other distributions i.e. Negative Binomial Regression, generalised poisson regression. Please refer SAS online documentation or Google for further information. HTH.  ... View more

This will be helpful Introduction to Regression Procedures Either proc reg or proc glm will do but dummy variables of your categorical variables are to be used in proc reg unlike proc glm where you just specify your categorical variables in the class statement. And proc reg has more regression model diagnostics features. ... View more

something like this?  data have; input var1 $ @@; datalines; 123 B23 3244 V190 ; run; data want; set have; if anyalpha(var1)>0 then do; var2=var1; call missing(var1); end; run; proc print data=want noobs; run; ... View more

Thanks @Reeza for pointing out. ... View more

how about try to include this few lines?  proc import ...; ...; ...; ...; DATAROW=2; GUESSINGROWS=32767; MIXED=YES; USEDATE=YES; SCANTIME=YES; ...; run; ... View more

or even this?   data DATASET_ORIGINAL; input ID INCOME1 INCOME2 INCOME3 VAR_INCOME_TO_UPDATE $ NEW_INCOME_VALUE; datalines; 1 100 200 150 INCOME2 201 2 400 250 250 INCOME1 99 3 300 210 165 INCOME2 188 3 800 320 155 INCOME2 178 ; run; data DATASET_COPY(keep=id income:); set DATASET_ORIGINAL; array INCOME{3}; do i=1 to 3; if VAR_INCOME_TO_UPDATE=vname(INCOME{i}) then INCOME{i}=NEW_INCOME_VALUE; end; run; proc print noobs; run;   ... View more

It could be due to the difference in method for computing the denominator degrees of freedom between both SAS and SPSS. As far as I know, the default is CONTAINment for SAS and Satterthwaite for SPSS. HTH. ... View more

Please try NOSPARSE in your proc surveymeans statement. ... View more