@fdsaaaa wrote: If your aim is to create an output dataset - try this: proc freq data=test ; table gender race/missing OUT=your_dataset; by age_group; run; If the objective is to not have anything appear in the Results window, or ods destination, then add the NOPRINT option to the Proc Freq statement. However you can only get ONE output data set per TABLES statement. And to get both variables per record you need both gender and race in the same table. proc freq data=test noprint; tables gender*race /missing OUT=your_dataset; by age_group; run; Or have the AGE_GROUP on the tables statement instead of BY: proc freq data=test noprint; tables age_group* gender*race /missing OUT=your_dataset; run;     ... View more

You only set the header in bold. See here for more examples, including setting styles for column variables. ... View more

This is a job for PROC SUMMARY   proc summary data=test nway; class treatment_group class term; types treatment_group*class treatment_group*class*term; var adult baby; output out=_stats_ max= n(adult)=n; run; data want; merge _stats_(where=(_type_=6) rename=(n=total_class_denominator) drop=term adult baby) _stats_(where=(_type_=7) rename=(n=event)); by treatment_group class; drop _type_ _freq_; run;   This is where PROC SUMMARY excels, when you need data aggregated at two (or more) different levels of aggregation. ... View more

Hi @monday89    You can also do this with Proc Sql:   proc sql; select group, category2, sum(binary) as binary, count(binary) as denominator from have group by group, category2; quit; Output:     ... View more

Hi @monday89    Another possibility, using only Proc Sql with an inner join to merge two queries:   proc sql; create table want as select a.*, b.total_event from (select treatment_group, AgeGroup, group1, group2, count(group1) as event from have group by treatment_group, AgeGroup,group1,group2) as a inner join (select treatment_group, AgeGroup, group1, group2, count(group1) as total_event from have group by treatment_group, AgeGroup,group1) as b on a.treatment_group=b.treatment_group and a.AgeGroup=b.AgeGroup and a.group1=b.group1 and a.group2=b.group2; run; ... View more

With SQL, use a cross join:   data names; input med_id med_name :$3.; datalines; 1 ABC 2 DEF 3 GHI 4 JKL 5 MNO 6 PQR 7 STU 8 VWX 9 YZ ; data meds; input patientId med_name :$3. medication; datalines; 123 ABC 1 123 GHI 1 123 JKL 1 123 PQR 1 456 DEF 1 456 GHI 1 ; proc sql; select a.patientId, b.med_name, coalesce(c.medication, 0) as medication from (select distinct patientId from meds) as a cross join (select distinct med_name from names) as b left join meds as c on a.patientId=c.patientId and b.med_name=c.med_name; quit; ... View more

Change: proc sql; create table test c as select group, max(CumulativeFrequency) as total from have; group by group; quit;   To:   proc sql; create table test as select *, max(CumulativeFrequency) as total from have group by group; quit;     ... View more

Use this code, replacing the PROC FREQ with your own code. First test it and see if it gives you a table you want, should run just as is. https://gist.github.com/statgeek/e0903d269d4a71316a4e   /*This code is an example of how to generate a table with Variable Name, Variable Value, Frequency, Percent, Cumulative Freq and Cum Pct No macro's are required Use Proc Freq to generate the list, list variables in a table statement if only specific variables are desired Use ODS Table to capture the output and then format the output into a printable table. */ *Run frequency for tables; ods table onewayfreqs=temp; proc freq data=sashelp.class; table sex age; run; *Format output; data want; length variable $32. variable_value $50.; set temp; Variable=scan(table, 2); Variable_Value=strip(trim(vvaluex(variable))); keep variable variable_value frequency percent cum:; label variable='Variable' variable_value='Variable Value'; run; *Display; proc print data=want(obs=20) label; run; @monday89 wrote: I have the following table below patientid trt gender race cad_history 1 group 1 F white 1 2 group 2 F white 1 3 group 1 M asian 0 4 group 1 F black 1 5 group 2 M asian 0     proc sort data=work.test; by trt; run;   ods output onewayfreqs=work.test2; proc freq data=work.test; table gender race cad_history /missing; by trt ; run; ods listing;   I get this:   trt Table gender gender Frequency Percent Cumulative Frequency CumulativePercent race race cad_history cad_history group 1 Table gender F F 2 66.67 2 66.67       . group 1 Table gender M M 1 33.33 3 100       . group 1 Table race     1 33.33 1 33.33 asian asian   . group 1 Table race     1 33.33 2 66.67 black black   . group 1 Table race     1 33.33 3 100 white white   . group 1 Table cad_history     1 33.33 1 33.33     0 0 group 1 Table cad_history     2 66.67 3 100     1 1 group 2 Table gender F F 1 50 1 50       . group 2 Table gender M M 1 50 2 100       . group 2 Table race     1 50 1 50 asian asian   . group 2 Table race     1 50 2 100 white white   . group 2 Table cad_history     1 50 1 50     0 0 group 2 Table cad_history     1 50 2 100     1 1 But then I have to polish it more to get this:   trt group 1 group 1 F number (%) number (%) M number (%) number (%) white number (%) number (%) asian number (%) number (%) black number (%) number (%) cad history 1 number (%) number (%) cad history 0 number (%) number (%)   Is there a simple way to do this? rather than writing additional commands? Thanks   ... View more

The function MEDIAN() works in SQL, but not P99 and not MODE. Also, PROC SUMMARY contains ability to compute confidence intervals and t-statistics and their probability. ... View more

Specify order=data assuming your order is specified. Otherwise your best bet is to recode them to numbers that will sort the way you want and apply a format to have the display labels you need. ... View more

See Example 8 here https://support.sas.com/resources/papers/proceedings/pdfs/sgf2008/173-2008.pdf   The link in the document to the code shows exactly how to do it. http://support.sas.com/rnd/papers/sgf2008/complex_reports.zip   @monday89 wrote: I have two datasets dataset #1: by group group_assigned denominator placebo 10 treatment 12   dataset #2:  Demographics treatment placebo Age     Gender     Race     Medications       the treatment groups changes every data export so i want to set n=# for each group. For this export, something like this:   Demographics treatment (n=12) placebo (n=10) Age     Gender     Race     Medications       I tried %macro but i think it is not working   ... View more

Thank you! I tried it but it showing me: Invalid DO loop control information, either the INITIAL or TO expression is missing or the BY        expression is missing, zero, or invalid"    I added "by" subject ID after "do", it wont work 😞 ... View more

data want; set have; if datepart(stop_date_time)>datepart(start_date_time) then new_stop_date=hdms(datepart(start_date_time),23,59,59); else new_stop_date=stop_date_time; run; Suggestion: spend some time reading the SAS documentation regarding date and datetime and time functions. https://documentation.sas.com/?cdcId=pgmmvacdc&cdcVersion=9.4&docsetId=allprodslang&docsetTarget=syntaxByCategory-function.htm&locale=en#p1b7ohfmgjqjexn1tdm9w63qi31e ... View more