The LSMEANS syntax provides the same estimates, but is less complex. It also solves the interaction issue. Thank you.  Do you know how I could derive a single p value for the interaction term? The Analysis Of GEE Parameter Estimates table has a p value for each level.  ... View more

Yes, multiplying the confidence limits. As an example, say I wanted standardized betas and confidence limits per the standard deviation. Or, say my independent variable was in years and I wanted to report it in decades (...a 1 unit change would be a decade, instead of a year).      ... View more

<The predictive margin is the average of the predicted values from all of the observations with joint_years fixed at a given value.>   The macro description seems to indicate that for predictors not included in the margins= statement, mean values are used for continuous variables and the reference level is used for categorical variables. And, there are ways to set these the values these predictors explicitly.   When I run the macro w/o setting any values, I get output that looks reasonable. I didn't set the reference level for any variables in the CLASS statement, however. According to the documentation: "Individual variable options (such as REF=) are not supported.".   How would the macro know what the reference levels were?  How would I explicitly set the value of continuous predictors, if I wanted to?    Thanks again for all your help.     ... View more

@StatDave I'm exploring the macro approach, but I'm fairly naive to SAS macros. I read the support article, and  downloaded the Margins macro definition. When I run it with the data step you provided, I get the Predictive Margins and the Differences of Margins. Great.   Just to confirm, if I wanted to compare the 95% percentile with the 50th percentile, for example, I would just replace the 5 and 15 in the DATA step with the values of the the 95% percentile with the 50th percentile, correct?              ... View more

@Ksharp Thanks. I have that syntax in my original post. It multiplies the beta by the number in the ESTIMATE statement, as you show. This is helpful, but it doesn't give me the adjusted means at 5 and 15 years (I now realize I used the wrong terminology in the original post. I'm looking for predicted values, as opposed to adjusted means).  ... View more

@PaigeMiller You are correct. I am asking for predicted values of the dependent variable at values of the independent variable that I specify. Apologies for the confusion.    Do I need to set reference categories for the variables in the CLASS statement? What about the continuous covariates?   Thanks.   ... View more

Thanks for the response and the helpful links.   Could you advise on how to use the LSMEANS, SLICE, or LSMESTIMATE statements to achieve the desired result? ... View more

I'm certainly willing to transform the dataset based on this guidance (assuming I can figure it out w/ all these variables). Wouldn't it be easier if I first subset the dataset to something more manageable?   Regarding my original objective(s): It looks like the synxtax below does what I want it to do. I'm sure there are better ways to do this, but in the spirit of @Reeza ("There's probably more efficient methods, but if this is one you understand and can edit/update yourself it's the easiest")...   Any chance you could take a quick look at the syntax below and let me know if you think anything looks objectively wrong?    proc sql noprint; select name into :colnames separated by ' ' /* Selects the name variable, which would typically contain column names.; */ /* It then places the selected names into a macro variable named colnames, with each name separated by a space.; */ from dictionary.columns /* This line specifies the source of the data, which is the dictionary.columns table in SAS. */ /* This is a special table that contains metadata about all available datasets, including column names. */ where /* Age */ substr(name,4) eq 'AGE' or /* Education */ substr(name,4) eq 'ED' or /* BMI */ substr(name,4) eq 'BMI' or /* Note: Neither BMI nor height nor weight are available in the data I have. */ /* Exam dates */ /* Not including exam date 35 (see below as J02EXDAT) */ substr(name,2) eq '02DATE' or /* Smoking status */ substr(name,2) eq '10SMOKE' and libname='CARDIA' /* Whatever libname is needed goes here, upper case */ and memname='C1260REQ06_29_2023' /* Your data set name goes here, upper case */ ; quit; /***********************************************************************************************************/ /* Creating a subset. */ /* &colnames (from above) is included in the KEEP statement. */ /***********************************************************************************************************/ data cardia.go; set CARDIA.C1260REQ06_29_2023; keep ID SHORT_ID SEX race /* Suffix Variables */ &colnames /* Preffix Variables */ CENTER: /* Per Lucia: The exam at Y35 was carried out in two phases. We are still discussing the best way to assemble a Reference File for this exam. */ /* We have variable J02EXDAT. */ J02EXDAT /* TAKING DIABETES MEDS (1=NO,2=YES) at baseline */ FDIABMED ; label J02EXDAT="DATE OF EXAM 10"; run; /* proc contents data=cardia.go varnum; run; */ /* proc print data=cardia.go (obs=10); run; */ /* ********************************************************************************************************* */ /* The syntax below allows for subsetting based on a prefix (i.e., exam year) */ /* ********************************************************************************************************* */ /* To subset for exam year 35: "J" */ proc sql noprint; select name into :colnames_j separated by ' ' from dictionary.columns where upcase(substr(name,1,1)) eq 'J' /* Your suffix goes here */ and libname='CARDIA' /* Whatever libname is needed goes here, upper case */ and memname='go' /* Your data set name goes here, upper case */ ; quit; data CARDIA.go_j; set CARDIA.go; keep ID SHORT_ID SEX race center30 /* Suffix Variables */ &colnames_j J02EXDAT ; run; proc contents data=cardia.go_j varnum; run; proc print data=cardia.go_j (obs=10); run; Thanks for your time and patience w/ me.    ... View more

I'm doing my best to figure this out. It's confusing for me and I appreciate all your help. I have a partial solution (below) that utilizes the approach provided by @PaigeMiller. proc sql noprint; select name into :colnames separated by ' ' /* Selects the name variable, which would typically contain column names.; */ /* It then places the selected names into a macro variable named colnames, with each name separated by a space.; */ from dictionary.columns /* This line specifies the source of the data, which is the dictionary.columns table in SAS. */ /* This is a special table that contains metadata about all available datasets, including column names. */ where /* Age */ substr(name,4) eq 'AGE' or /* Education */ substr(name,4) eq 'ED' or /* BMI */ substr(name,4) eq 'BMI' or /* Note: Neither BMI nor height nor weight are available in the data I have. */ /* Exam dates */ /* Not including exam date 35 (see below as J02EXDAT) */ substr(name,2) eq '02DATE' or /* Smoking status */ substr(name,2) eq '10SMOKE' and libname='CARDIA' /* Whatever libname is needed goes here, upper case */ and memname='C1260REQ06_29_2023' /* Your data set name goes here, upper case */ ; quit; /***********************************************************************************************************/ /* Creating a subset. */ /* &colnames (from above) is included in the KEEP statement. */ /***********************************************************************************************************/ data cardia.go; set CARDIA.C1260REQ06_29_2023; keep ID SHORT_ID SEX race /* Suffix Variables */ &colnames /* Preffix Variables */ CENTER: /* Per Lucia: The exam at Y35 was carried out in two phases. We are still discussing the best way to assemble a Reference File for this exam. */ /* We have variable J02EXDAT. */ J02EXDAT /* TAKING DIABETES MEDS (1=NO,2=YES) at baseline */ FDIABMED ; label J02EXDAT="DATE OF EXAM 10"; run; The above syntax allows me to use a list based on a suffix in a KEEP statement to create a subset (per my original post).    I would also like to be able to subset by prefix (e.g., subset all the variables from a particular timepoint; "A" = baseline). @Tom offered an approach that looks like it might offer that, but I can't figure out how to go from the PROC SQL to a dataset. When I run a PROC PRINT on the "groups" dataset the variables are all under the column "names" and the other columns are all the metadata categories:  Using what I've adapted from @PaigeMiller above (because at least I understand that part), Is there a way to create a variable that would allow me to subset by prefix?  data cardia.go_a; set cardia.go; where prefix = "A"; run; Thanks for your help.  ... View more

Here is what my primitive SAS brain was thinking:  &colnames is a macro variable for the list of variables w/ a suffix of SMOKE.  &colnames2 is a macro variable for the list of variables w/ a suffix of TEST, etc.   I'm sure there are better ways of doing this, but I was asking about writing a separate proc sql for each list of variables (&colnames2=age, &colnames3=physical activity, &colnames4=alcohol use, etc.). proc sql noprint; select name into :colnames separated by ' ' from dictionary.columns where substr(name,4) eq 'SMOKE' /* Your suffix goes here */ and libname='CARDIA' /* Whatever libname is needed goes here, upper case */ and memname='C1260REQ06_29_2023' /* Your data set name goes here, upper case */ ; quit; proc sql noprint; select name into :colnames2 separated by ' ' from dictionary.columns where substr(name,4) eq 'TEST' /* Your suffix goes here */ and libname='CARDIA' /* Whatever libname is needed goes here, upper case */ and memname='C1260REQ06_29_2023' /* Your data set name goes here, upper case */ ; quit; data new_dataset; set CARDIA.C1260REQ06_29_2023; keep &colnames &colnames2 ID; run;     ... View more