@CathyVI wrote: @FreelanceReinh  What is this step doing in the code? Is it counting the location of event. if _vn<3 then event_type=' '||event_type; /* Indentation improves sort order of report columns. */ Duration=e[_vn]; The purpose of the IF-THEN statement is to indent the character values "Event1 only" and "Event2 only" by one character (resulting in " Event1 only" and " Event2 only") so that they come first in alphabetical order. The inserted leading blank is sorted before all letters. Without this trick the column order in the final PROC FREQ output would be Case32 only, Event1 only, Event2 only, Event46 A only, Event46 B only, Event46 C only, Multiple If this alphabetical column order is acceptable, remove that IF-THEN statement to simplify the code.   The statement Duration=e[_vn]; assigns the non-zero value among the four values of Event1, Event2, Case32 and Event46 to variable Duration. There is exactly one non-zero value because of the IF condition _n0=3. Example: If Case32=2 and Event1=Event2=Event46=0, the concatenation _s equals "0020". The COUNTC function (here counting zeros in _s) then returns _n0=3 and the VERIFY function returns _vn=3 as the position of the first character in _s that is not equal to "0". Finally, e[_vn]=e[3] is the value of the third variable of the list event1 event2 case32 event46 in the ARRAY statement, i.e., the value of Case32 (which is 2 in the example).   what is the difference between Duration=e[_vn];  and  _v=vname(e[_vn]); The VNAME function retrieves the name of the variable corresponding to the array reference e[_vn]. In the example above (where _vn=3) the result is _v="Case32".   Then is this code going to identify only multiple of 2 Duration=1+(countc(_s,'2')>1); /* Duration=2 only in case of multiple occurrences of value 2. */ In the case event_type='Multiple' the question arises whether this observation should be counted in category "<=30 days" or in "31-60 days" if both categories occur, e.g., if Event1=0, Event2=1, Case32=2, Event46=0. From your description "if you have 2 in more than one group you will be multi_60" I concluded that this particular example should be counted in "<=30 days", whereas, e.g., an observation with Event1=2, Event2=1, Case32=2, Event46=0 would be counted in "31-60 days" (because value 2 occurs more than once). This rule is implemented in the assignment statement Duration=1+(countc(_s,'2')>1); Step-by-step explanation: Event1=0, Event2=1, Case32=2, Event46=0 → _s="0120" → countc(_s,'2')=1 → 1>1 is FALSE (0) → Duration=1+0=1 Event1=2, Event2=1, Case32=2, Event46=0 → _s="2120" → countc(_s,'2')=2 → 2>1 is TRUE (1) → Duration=1+1=2 That assignment statement using a Boolean expression (the inequality countc(_s,'2')>1), which evaluates to TRUE (numeric value: 1) or FALSE (numeric value: 0), is an abbreviation for if countc(_s,'2')>1 then Duration=2; else Duration=1; Note that this logic is applied only in the case _n0<3, not to observations with, e.g., Event1=0, Event2=0, Case32=2, Event46=0, where _n0=3 (and eventually Duration=2) as explained further above. ... View more

@Patrick wrote: I couldn't find a SAS informat that can directly convert the source string to a SAS datetime value ... Informat NLDATM. works for me with system option LOCALE=DE_DE. ... View more

Hi @ChrisWoo,   Basically, the PUT statement works only with variables and string constants. Results of a function must be stored in a variable first. data _null_; do i = 0 to 7; text=put(intnx("month","01Jul2023"d,i,"end"),ddmmyy10.); put "text = " text; end; run; With named output the PUT statement can be simplified to put text=; This doesn't put blanks around the equals signs, though.   Another option is formatted output: data _null_; do i = 0 to 7; d=intnx("month","01Jul2023"d,i,"end"); put "text = " d ddmmyy10.; end; run; ... View more

Also, have you already tried some of the suggestions from the Reddit thread you copied your post from, e.g., to "aggregate the 100+ categories into a smaller set of categories"? ... View more

@CathyVI wrote: This is the overall goal am trying to get.   Event1 only Event2 only Case32 only Event46 A only Event46 B only Event46 C Only Multiple Total 30 days                 31-60 days                 Total                 This looks like a two-way frequency table, so we need to create a second variable, let's call it Duration, in addition to event_type. Then we can use PROC FREQ to obtain such a table (which, in turn, could be used as a basis for a more sophisticated report).   Let me first create a more comprehensive sample dataset which includes all possible combinations of events and duration values (that have been mentioned so far).   /* Create a comprehensive sample dataset */ data have; call streaminit(31415927); do Event1=0 to 2; do Event2=0 to 2; do Case32=0 to 2; do Event46=0 to 2; if Event46 then do grp='A', 'B', 'C'; do _n_=1 to rand('integer',9); output; end; end; else do; grp=' '; do _n_=1 to rand('integer',9); output; end; end; end; end; end; end; run; /* Define a format for variable Duration */ proc format; value days 1=' <=30 days' 2='31-60 days'; run; /* Create the analysis dataset */ data want(drop=_:); set have; array e[*] event1 event2 case32 event46; length _s $4 _v event_type $40; _s=cat(of e[*]); _n0=countc(_s,'0'); if _n0=3 then do; /* Three zeros indicate that only one type of event has occurred. */ _vn=verify(_s,'0'); /* This determines which type of event it was. */ _v=vname(e[_vn]); event_type=catx(' ',_v,grp,'only'); if _vn<3 then event_type=' '||event_type; /* Indentation improves sort order of report columns. */ Duration=e[_vn]; end; else if _n0<3 then do; /* Fewer than 3 zeros indicate that multiple types of events have occurred. */ event_type='Multiple'; Duration=1+(countc(_s,'2')>1); /* Duration=2 only in case of multiple occurrences of value 2. */ end; format Duration days.; run; /* Generate a simple report */ proc freq data=want order=formatted; tables duration*event_type / nopercent norow nocol; run; Result:   The six missing values are from observations with Event1=Event2=Case32=Event46=0. The value of Duration for event_type='Multiple' is determined according to your specification "if you have 2 in more than one group you will be multi_60." ... View more

@CathyVI wrote: I would like my outcome to have the event46 outcomes in their respective groups. So you want to split the count of "event46" into counts of the subgroups "event46 A", "event46 B", etc.? A simple solution would be to modify the value of event_type in Reeza's code accordingly, e.g., insert as the last statement in the DATA step creating dataset WANT: if event_type='event46' then event_type=catx(' ','event46',grp); However, this might not suffice for a fancier report with, say, headers "A", "B", "C" and a spanning header "event46". ... View more

@CathyVI wrote: My table is not (.) it is (0). Also, my columns have different names. Reeza's definition of variable event_type is a great idea for these new requirements and, of course, using the SUM function instead of the N function. ... View more

@CathyVI wrote: @FreelanceReinh how can I add "Total" to the output table you created.  Only1 Only2 Only3 Only4 Multi Total 2 2  2 1 4 11 I would compute the total in the DATA step and then add the computed variable to the COLUMN statement of the PROC REPORT step: data want(drop=_c); set have; array only[4]; _c=n(of event:); if _c>1 then multi=1; else if _c=1 then only[whichn(1,of event:)]=1; total=sum(of only[*], multi, 0); run; proc report data=want; column only: multi total; run; The purpose of the zero in the third argument of the SUM function is to avoid log messages about missing values for (hypothetical) observations with missing values in all event... variables. ... View more

Hello @mt88,   You could use PROC SQL to add a constant variable to the ODS output dataset containing the percentage of cells with expected frequency less than 5: ods output chisq=tst crosstabfreqs=ctf; proc freq data = combinedIDmanu; tables fentanyl*num_doc_vis_catB/chisq expected; run; proc sql; create table want as select * from tst, (select mean(.<expected<5) as expected_lt_5 format=percent6.0 from ctf where _type_='11'); quit;   ... View more

Hello @CathyVI,   If the values of event1, event2, etc.  are either 1 or missing, you can count the non-missing values with the N function and then use the WHICHN function to populate the "only..." variables. The report is easy with PROC REPORT.   data want(drop=_c); set have; array only[4]; _c=n(of event:); if _c>1 then multi=1; else if _c=1 then only[whichn(1,of event:)]=1; run; proc report data=want; column only: multi; run; Note that variable names only1, only2, etc. with a numeric suffix are more convenient to work with than event1only, etc.: see the array definition and the variable list in the COLUMN statement. ... View more

@CHELS wrote: Then for the part highlighted in red below, should it be input as 0.7 (0.6+0.1) or just 0.1? I would say 0.9 (=1−0.1) because 10% loss to follow-up leaves 90% of the subjects participating in the study and the processes determining survival and loss to follow-up are assumed to be independent. ... View more

@mgx wrote: Hi FreelanceReinh,    My matrix is symmetric until about 9 decimal points or so. Hence, it is a rounding issue and I am looking for a way to decrease the number of decimal points of the matrix. I assumed that Sigma=round(inv(J)*K*inv(J),0.001); ensures that all values are rounded to three decimal places (couldn't test it, though, for lack of a SAS/IML license).   Can you show one of the pairs of off-diagonal elements in COV_IMPUT that make the variance-covariance matrix for _imputation_=1 asymmetric? ... View more