I am trying to adapt Method 4 in this paper to calculate the duration of many observations, but discounting overlapping dates: https://support.sas.com/resources/papers/proceedings/proceedings/sugi31/048-31.pdf
For example, two rows of observations for subject 101 lasting from 2017-03-02 to 2017-03-16 and 2017-03-04 to 2017-03-17 respectively should return a value of only 16 days.
I am getting an error with the dates being 'Invalid numeric data', though, resulting in later errors. I have tried format startdate yyyymmdd10.; and format stopdate yyyymmdd10.; with no success.
Can anyone help me properly format my dates for use here, or identify any further errors?
Edit: Line 80 refers to do xdate = startdate to stopdate;.
I am still unable to convert or create the date variables as numeric/date values. I have used the following code:
data sasuser.Mdm;
set sasuser.Mdm;
do xdate = input(Startdate,yymmdd10.) to input(stopdate,yymmdd10.);
put xdate= yymmdd10.;
output;
end;
run;
To get this output:
1 data sasuser.Mdm;
2 set sasuser.Mdm;
3 do xdate = input(Startdate,yymmdd10.) to input(stopdate,yymmdd10.);
4 put xdate= yymmdd10.;
5 output;
6 end;
7 run;
xdate=2017-03-02
xdate=2017-03-03
xdate=2017-03-04
xdate=2017-03-05
xdate=2017-03-06
xdate=2017-03-07
xdate=2017-03-08
xdate=2017-03-09
xdate=2017-03-10
xdate=2017-03-11
xdate=2017-03-12
xdate=2017-03-13
xdate=2017-03-14
xdate=2017-03-15
xdate=2017-03-16
xdate=2017-03-04
xdate=2017-03-05
xdate=2017-03-06
xdate=2017-03-07
xdate=2017-03-08
xdate=2017-03-09
xdate=2017-03-10
xdate=2017-03-11
xdate=2017-03-12
xdate=2017-03-13
xdate=2017-03-14
xdate=2017-03-15
xdate=2017-03-16
xdate=2017-03-17
xdate=2017-03-07
xdate=2017-03-08
xdate=2017-03-09
xdate=2017-03-10
xdate=2017-03-11
xdate=2017-03-12
xdate=2017-03-13
xdate=2017-03-14
xdate=2017-03-15
xdate=2017-03-16
xdate=2017-03-17
xdate=2017-03-18
xdate=2017-03-19
xdate=2017-03-20
xdate=2017-03-21
xdate=2017-02-08
xdate=2017-02-09
xdate=2017-02-10
xdate=2017-02-11
xdate=2017-02-12
xdate=2017-02-13
xdate=2017-02-14
xdate=2017-02-15
xdate=2017-02-16
xdate=2017-02-17
xdate=2017-02-18
xdate=2017-02-19
xdate=2017-02-20
xdate=2017-02-21
xdate=2017-02-22
xdate=2017-02-23
xdate=2017-02-24
xdate=2017-02-23
xdate=2017-02-24
xdate=2017-02-25
xdate=2017-02-26
xdate=2017-02-27
xdate=2017-02-28
xdate=2017-03-01
xdate=2017-03-02
xdate=2017-03-03
xdate=2017-03-04
xdate=2017-03-05
xdate=2017-03-06
xdate=2017-03-07
xdate=2017-03-08
xdate=2017-02-26
xdate=2017-02-28
xdate=2017-03-13
xdate=2017-03-17
xdate=2017-03-25
xdate=2017-03-28
xdate=2017-03-23
xdate=2017-03-24
xdate=2017-03-25
xdate=2017-03-26
xdate=2017-03-27
xdate=2017-03-28
xdate=2017-03-29
xdate=2017-03-30
xdate=2017-03-29
xdate=2017-04-03
xdate=2017-04-04
xdate=2017-04-03
xdate=2017-04-04
xdate=2017-04-05
xdate=2017-04-05
xdate=2017-04-06
xdate=2017-04-06
xdate=2017-04-07
xdate=2017-03-25
xdate=2017-03-26
xdate=2017-03-30
xdate=2017-04-01
xdate=2017-04-02
xdate=2017-04-03
xdate=2017-04-04
xdate=2017-04-08
xdate=2017-04-09
xdate=2017-04-10
xdate=2017-04-11
xdate=2017-04-12
xdate=2017-04-12
xdate=2017-04-13
xdate=2017-04-13
xdate=2017-04-14
xdate=2017-04-15
xdate=2017-04-16
xdate=2017-04-17
xdate=2017-04-18
xdate=2017-04-19
xdate=2017-04-20
xdate=2017-04-21
xdate=2017-04-22
xdate=2017-04-19
xdate=2017-04-23
xdate=2017-04-24
xdate=2017-04-25
xdate=2017-04-26
xdate=2017-04-26
xdate=2017-04-27
xdate=2017-04-28
xdate=2017-05-05
xdate=2017-05-06
xdate=2017-05-16
xdate=2017-05-19
xdate=2017-05-20
xdate=2017-05-21
xdate=2017-05-22
xdate=2017-05-19
xdate=2017-05-20
xdate=2017-05-21
xdate=2017-05-22
xdate=2017-05-23
xdate=2017-05-24
xdate=2017-05-25
xdate=2017-05-26
xdate=2017-05-22
xdate=2017-05-23
xdate=2017-05-24
xdate=2017-05-25
xdate=2017-05-26
xdate=2017-05-27
xdate=2017-05-28
xdate=2017-05-29
xdate=2017-05-30
xdate=2017-05-31
xdate=2017-06-01
xdate=2017-06-02
xdate=2017-06-03
xdate=2017-06-04
xdate=2017-06-05
xdate=2017-06-06
xdate=2017-06-07
xdate=2017-06-08
xdate=2017-06-09
xdate=2017-06-10
xdate=2017-06-11
xdate=2017-06-12
xdate=2017-06-13
xdate=2017-06-14
xdate=2017-06-15
xdate=2017-06-16
xdate=2017-06-17
xdate=2017-06-18
xdate=2017-06-19
xdate=2017-06-20
xdate=2017-06-21
xdate=2017-06-22
xdate=2017-06-23
xdate=2017-06-24
xdate=2017-06-25
xdate=2017-06-26
xdate=2017-06-27
xdate=2017-06-28
xdate=2017-06-29
xdate=2017-06-30
xdate=2017-07-01
xdate=2017-07-02
xdate=2017-07-03
xdate=2017-07-04
xdate=2017-07-05
xdate=2017-07-06
xdate=2017-07-07
xdate=2017-07-08
xdate=2017-07-09
xdate=2017-07-10
xdate=2017-07-11
xdate=2017-07-12
xdate=2017-07-13
xdate=2017-07-14
xdate=2017-07-15
xdate=2017-07-16
xdate=2017-07-17
xdate=2017-07-18
xdate=2017-07-19
xdate=2017-07-20
xdate=2017-07-21
xdate=2017-07-22
xdate=2017-07-23
xdate=2017-07-24
xdate=2017-07-25
xdate=2017-07-26
xdate=2017-07-27
xdate=2017-07-28
xdate=2017-07-29
xdate=2017-07-30
xdate=2017-07-31
xdate=2017-08-01
xdate=2017-08-02
xdate=2017-08-03
xdate=2017-08-04
xdate=2017-08-05
xdate=2017-08-06
xdate=2017-08-07
xdate=2017-08-08
xdate=2017-08-09
xdate=2017-08-10
xdate=2017-08-11
xdate=2017-08-12
xdate=2017-08-13
xdate=2017-08-14
xdate=2017-08-15
xdate=2017-08-16
xdate=2017-08-17
xdate=2017-08-18
xdate=2017-08-19
xdate=2017-08-20
xdate=2017-08-21
xdate=2017-08-22
xdate=2017-08-23
xdate=2017-08-24
xdate=2017-08-25
xdate=2017-08-26
xdate=2017-08-27
xdate=2017-08-28
xdate=2017-08-29
xdate=2017-08-30
xdate=2017-08-31
xdate=2017-09-01
xdate=2017-05-27
xdate=2017-05-28
xdate=2017-05-29
xdate=2017-05-30
xdate=2017-05-31
xdate=2017-06-01
xdate=2017-06-02
xdate=2017-06-03
xdate=2017-06-04
xdate=2017-06-05
xdate=2017-06-06
xdate=2017-06-07
xdate=2017-06-08
xdate=2017-06-09
xdate=2017-06-10
xdate=2017-06-11
xdate=2017-06-12
xdate=2017-06-13
xdate=2017-06-14
xdate=2017-06-15
xdate=2017-06-16
xdate=2017-06-17
xdate=2017-06-18
xdate=2017-06-19
xdate=2017-06-20
xdate=2017-06-21
xdate=2017-06-22
xdate=2017-06-23
xdate=2017-06-24
xdate=2017-06-25
xdate=2017-06-26
xdate=2017-06-27
xdate=2017-06-28
xdate=2017-06-29
xdate=2017-06-30
xdate=2017-07-01
xdate=2017-07-02
xdate=2017-07-03
xdate=2017-07-04
xdate=2017-07-05
xdate=2017-07-06
xdate=2017-07-07
xdate=2017-07-08
xdate=2017-07-09
xdate=2017-07-10
xdate=2017-07-11
xdate=2017-07-12
xdate=2017-07-13
xdate=2017-07-14
xdate=2017-07-15
xdate=2017-07-16
xdate=2017-07-17
xdate=2017-07-18
xdate=2017-07-19
xdate=2017-07-20
xdate=2017-07-21
xdate=2017-07-22
xdate=2017-07-23
xdate=2017-07-24
xdate=2017-07-25
xdate=2017-07-26
xdate=2017-07-27
xdate=2017-07-28
xdate=2017-07-29
xdate=2017-07-30
xdate=2017-07-31
xdate=2017-08-01
xdate=2017-08-02
xdate=2017-08-03
xdate=2017-08-04
xdate=2017-08-05
xdate=2017-08-06
xdate=2017-08-07
xdate=2017-08-08
xdate=2017-08-09
xdate=2017-08-10
xdate=2017-08-11
xdate=2017-08-12
xdate=2017-08-13
xdate=2017-08-14
xdate=2017-08-15
xdate=2017-08-16
xdate=2017-08-17
xdate=2017-08-18
xdate=2017-08-19
xdate=2017-08-20
xdate=2017-08-21
xdate=2017-08-22
xdate=2017-08-23
xdate=2017-08-24
xdate=2017-08-25
xdate=2017-08-26
xdate=2017-08-27
xdate=2017-08-28
xdate=2017-08-29
xdate=2017-08-30
xdate=2017-08-31
xdate=2017-09-01
xdate=2017-06-14
xdate=2017-06-15
xdate=2017-06-16
xdate=2017-06-17
xdate=2017-06-18
xdate=2017-06-19
xdate=2017-06-20
xdate=2017-06-21
xdate=2017-06-22
xdate=2017-06-23
xdate=2017-06-24
xdate=2017-06-25
xdate=2017-06-26
xdate=2017-06-27
xdate=2017-06-28
xdate=2017-06-29
xdate=2017-06-14
xdate=2017-06-15
xdate=2017-06-16
xdate=2017-06-17
xdate=2017-06-18
xdate=2017-06-19
xdate=2017-06-20
xdate=2017-06-21
xdate=2017-06-22
xdate=2017-06-23
xdate=2017-06-24
xdate=2017-06-25
xdate=2017-06-26
xdate=2017-06-27
xdate=2017-06-28
xdate=2017-06-29
xdate=2017-03-27
xdate=2017-04-02
xdate=2017-04-07
xdate=2017-04-08
xdate=2017-04-09
xdate=2017-04-13
xdate=2017-04-14
xdate=2017-04-15
xdate=2017-04-16
xdate=2017-04-17
xdate=2017-04-19
xdate=2017-04-20
xdate=2017-04-21
xdate=2017-04-22
xdate=2017-04-23
xdate=2017-04-24
xdate=2017-04-20
xdate=2017-04-21
xdate=2017-04-22
xdate=2017-04-23
xdate=2017-04-24
xdate=2017-04-25
xdate=2017-04-26
xdate=2017-04-27
xdate=2017-04-28
xdate=2017-04-29
xdate=2017-04-30
xdate=2017-05-01
xdate=2017-05-02
xdate=2017-04-24
xdate=2017-04-25
xdate=2017-04-26
xdate=2017-04-27
xdate=2017-04-28
xdate=2017-04-29
xdate=2017-04-30
xdate=2017-05-01
xdate=2017-05-02
xdate=2017-05-03
xdate=2017-05-04
xdate=2017-05-05
xdate=2017-05-06
xdate=2017-05-07
xdate=2017-05-08
xdate=2017-05-09
xdate=2017-05-10
xdate=2017-05-11
xdate=2017-05-12
xdate=2017-05-13
xdate=2017-05-14
xdate=2017-05-15
xdate=2017-05-16
ERROR: Invalid DO loop control information, either the INITIAL or TO expression is missing or the
BY expression is missing, zero, or invalid.
SUBJID=106 KEY=106-9 OBS=9 TOTAL=12 STARTDATE=2017-04-25 STOPDATE= CLASS=Steroid / Diuretic
xdate=20934 _ERROR_=1 _N_=52
NOTE: The SAS System stopped processing this step because of errors.
NOTE: There were 52 observations read from the data set SASUSER.MDM.
WARNING: The data set SASUSER.MDM may be incomplete. When this step was stopped there were 431
observations and 8 variables.
WARNING: Data set SASUSER.MDM was not replaced because this step was stopped.
NOTE: DATA statement used (Total process time):
real time 0.38 seconds
cpu time 0.29 seconds```
I don't understand why input doesn't appear to be working. Dates are still listed as character strings under column attributes. The do part also isn't working as intended. I'd be grateful for any further guidance.
Do not use the same name in the DATA and SET statement. Then you're always having to rebuild from the start.
Convert your start and stop date to SAS dates
Remove PUT
Add formats to see them displayed as desired
Drop old variables to avoid confusion.
Your two code steps, the data step and SQL do not appear related. Not sure why you would even need a list of dates for intervals or anything. There are much better ways to calculate an overlap. I think you're putting us through an xy problem where it would be significantly easier to show us what you're attempting to do and people would be able to provide a much better solution.
data sasuser.Mdm2; /*1*/
set sasuser.Mdm;
/*2*/
start_date = input(startdate, yymmdd10.);
end_date = input(stopdate, yymmdd10.);
do xdate = start_date to stop_date;
output; /*3*/
end;
/*4*/
format start_date end_date xDate yymmdd10.;
/*5*/
drop startdate stopdate;
run;
*check;
proc contents data=sasuser.mdm2;
run;
EDIT: Also, if you had some sort of grouping variable to indicate that these were part of the same episode you could then just take the min/max of the dates and subtract them to get the interval duration for starters. Grouping via a data step is trivial.
data want;
set have;
by id;
retain episode;
start_date = input(start_date, yymmdd10.);
end_date = input(stopdate, yymmdd10.);
prev_stop_date = lag(stopDate);
if first.id then do;
episode = 0;
call missing(prev_stop_date);
end;
if not (start_date <=prev_stop_date <= end_date) then episode+1;
*could add in logic to calculate dates and durations as well depending....;
run;
It sounds like your SAS log is complaining about this statement.
do xdate=startdate to stopdate;
Because STARTDATE and STOPDATE are character strings instead of dates.
Make sure to create your date values as dates instead of character strings.
Tom's correct, of course, the startdate and stopdate seem to be characters.
To properly use this, do something like this (only the do loop is relevant for you, the rest is to show it working):
data _null_;
startdate = '2017-03-02';
stopdate = '2017-03-16';
do xdate = input(Startdate,yymmdd10.) to input(stopdate,yymmdd10.);
put xdate= yymmdd10.; *just put to the log to see what you are getting;
end;
run;
input will convert the text to a numeric value. Do realize you have to format that xdate as a date format if you want to be able to view it - if you're just using it as an input, though, you can leave the formatting off.
Related
I want to display my data as either yes or no in the output for initaltesting, site visit, and follow up, how would I do that? There are numeric values for this on the data set but want character responses of "y" or "n"
PROC FORMAT;
VALUE SiteVisitfmt 1 = 'yes'
0 = 'no';
VALUE InitialTestingfmt 1 = 'yes'
2 = 'no';
VALUE TestEventfmt 1 = 'One Event '
2 = 'Two Events'
3 = 'Three Events'
4 = 'Four Events'
5 = 'Five Events';
VALUE FollowUpfmt 1 = 'yes'
0 = 'no';
FORMAT SiteVisit SiteVisitfmt. InitialTesting InitialTestingfmt. TestEvent TestEventfmt.
FollowUp FollowUpfmt.;
RUN;
data PMdataedits;
set PMdata (rename = (Number_of_Days_from_Onset_to_Sit =SiteVisit
Number_of_Days_between_Onset_and = InitialTesting
Number_of_Test_Events_in_IRIS = TestEvent
Number_of_Days_between_Test_1_an = FollowUp));
drop SPA;
attrib date1 format=date9.;
date1=input(date,mmddyy10.);
NewSiteVisit = put(SiteVisit, 8.);
NewInitialTesting = put(InitialTesting, 8.);
NewFollowUp = put(FollowUp, 8.);
NewSiteVisit=;
if (NewSiteVisit=<1) THEN NewSiteVisit= '1';
if (NewSiteVisit>1) THEN NewSiteVist= '0';
NewInitialTesting=;
if (NewInitialTesting<=2) THEN NewInitialTesting= '1';
if (NewInitialTesting>2) THEN NewInitialTesting='0';
This statement:
FORMAT SiteVisit SiteVisitfmt. InitialTesting InitialTestingfmt. TestEvent TestEventfmt.
FollowUp FollowUpfmt.;
Needs to be on the data step (sometime after data PMdataedits; but before the run; that you don't show), not in the proc format. That's the statement that assigns the format to a variable; each dataset (which is defined by a data step) has its own, unique set of variables that can be the same name as other datasets but have different contents and formats.
Also note that you don't have to name the formats after the variables, and don't need three different yes/no formats. You could have done:
proc format;
format ynf
'1'='yes'
'0'='no'
;
run;
And then used
format sitevisit initialtesting followup ynf.;
And that would have covered all three of them with one format. But what you did is legal, it's just more typing than you need!
I have a dataset which is like this:
new_fish old_fish
1 2
4
3
And I want to make a column called status, where if new_fish is empty call it dead, and if old_fish is empty call it born, and if neither are empty call it alive.
I would want it to look like this:
new_fish old_fish status
1 2 alive
4 dead
3 born
I've tried the following code in sas,
data diff_withclass;
set diff;
if missing(new_fish) then status= 'dead';
if missing(old_fish) then status= 'born';
else status = 'alive';
run;
However, this doesn't work. It just sets status to alive.
ANy suggestions would be great.
You need to use else if. The second if statement is overwriting the first.
data diff_withclass;
set diff;
if missing(new_fish) then status= 'dead';
else if missing(old_fish) then status= 'born';
else status = 'alive';
run;
A useful construction is select, when you're choosing one of a list of options. Sometimes you select a varialbe:
select(var);
when (1) do something; *if var=1 then ... ;
when (2) do something; *else if var=2 then ... ;
otherwise do something; *else ... ;
end;
However, it can be used alone also, as in your case.
data diff_withclass;
set diff;
length status $5;
select;
when (missing(new_fish)) status= 'dead';
when (missing(old_fish)) status= 'born';
otherwise status = 'alive';
end;
run;
Another useful construction is the ifc function. This works like Excel's if, in that it takes an argument that is a boolean (so, the "if" part), if that is true it returns the second argument, and if it is false it returns the third argument. Here we can nest two of them to get your result.
data diff_ifc;
set diff;
length status $5;
status = ifc(missing(new_fish),'dead',ifc(missing(old_fish),'born','alive'));
run;
Finally, there is the good old "boolean arithmetic" solution. Here we create a numeric, and you can then turn that into a character if you prefer, or just use a user-defined format, which is really the optimal way to handle this anyway. This takes advantage of the fact that "true" evaluates to 1 and "false" to 0 in SAS, so we just add up the values, and arbitrarily call Dead the 2 and Born the 1 (could do the opposite, or even have Dead=-1, Born=1, Alive=0, by multiplying by -1 for Dead).
proc format;
value statusf
0 = 'Alive'
1 = 'Born'
2 = 'Dead'
;
quit;
data diff_bool;
set diff;
status = missing(new_fish)*2 + missing(old_fish);
format status statusf.;
run;
Variable name is PRC. This is what I have so far. First block to delete negative values. Second block is to delete missing values.
data work.crspselected;
set work.crspraw;
where crspyear=2016;
if (PRC < 0)
then delete;
where ticker = 'SKYW';
run;
data work.crspselected;
set work.crspraw;
where ticker = 'SKYW';
where crspyear=2016;
where=(PRC ne .) ;
run;
Instead of using a function to remove negative and missing values, it can be done more simply when inputting or outputting the data. It can also be done with only one data step:
data work.crspselected;
set work.crspraw(where = (PRC >= 0 & PRC ^= .)); * delete values that are negative and missing;
where crspyear = 2016;
where ticker = 'SKYW';
run;
The section that does it is:
(where = (PRC >= 0 & PRC ^= .))
Which can be done for either the input dataset (work.crspraw) or the output dataset (work.crspselected).
If you must use a function, then the function missing() includes only missing values as per this answer. Hence ^missing() would do the opposite and include only non-missing values. There is not a function for non-negative values. But I think it's easier and quicker to do both together simultaneously without a function.
You don't need more than your first test to remove negative and missing values. SAS treats all 28 missing values (., ._, .A ... .Z) as less than any actual number.
I have a column of format DATETIME23. like this:
14.02.2017 13:00:25
I want to conver it to a string, so later, i would be able to modern it, so, for example, the final version would look like:
2017-02-14 13:00:25.000
Problem occures, when i try to convert date to char format: in result i have a string of smth like 1802700293 - which is the number of seconds.
I tried:
format date $23.0
or
date = put(date, $23.0)
P.S This is nother try:
data a;
format d date9.;
d = '12jan2016'd;
dtms = cat(day(d),'-',month(d),'-',year(d),' 00:00:00.000');
/* если нужно обязательно двухзначные день и месяц, то такой колхоз: */
if day(d) < 10 then dd=cat('0',put(day(d),$1.));
else ddday=put(day(d),$2.);
if month(d) < 10 then mm=cat('0',put(month(d),$1.));
else mm=put(month(d),$2.);
yyyy=put(year(d),$4.);
/*dtms2 = cat(dd,'-',mm,'-',yyyy,' 00:00:00.000');*/
dtms2 = cat(dd,'-',mm,'-',yyyy,' 00:00:00.000');
dtms = cat(day(d),'-',month(d),'-',year(d),' 00:00:00.000');
run;
BUT, abnormally, the dtms2 concat destroys the zero in the month element
If your datetime is stored as a SAS datetime, just use the appropriate format :
data test ;
dt = '09feb2017:13:53:26'dt ; /* specify a datetime constant */
new_dt = put(dt,E8601DT23.3) ; /* ISO datetime format */
run ;
Output
dt new_dt
1802267606 2017-02-09T13:53:26.000
If you need to replace the 'T' with a space, simply add a translate function around the put().
For your dtms solution you can use put and the Z2. format to keep the leading zero when you concatenate:
dtms = cat(day(d),'-', put(month(d),z2.),'-',year(d),' 00:00:00.000');
You should be able to just use put(date, datetime23.) for your problem though instead of $23, which is converting the number of seconds to a string with length 23. However, as a comment has mentioned datetime23. is not the format from your example.
As a follow up to this question, for which my existing answer appears to be best:
Extracting sub-data from a SAS dataset & applying to a different dataset
Given a dataset dsn_in, I currently have a set of macro variables max_1 - max_N that contain numeric data. I also have a macro variable varlist containing a list of variables. The two sets of macros are related such that max_1 is associated with scan(&varlist, 1), etc. I am trying to do compare the data values within dsn_in for each variable in varlist to the associated comparison values max_1 - max_N. I would like to output the updated data to dsn_out. Here is what I have so far:
data dsn_out;
set dsn_in;
/* scan list of variables and compare to decision criteria.
if > decision criteria, cap variable */
do i = 1 by 1 while(scan(&varlist, i) ~= '');
if scan("&varlist.", i) > input(symget('max_' || left(put(i, 2.))), best12.) then
scan("&varlist.", i) = input(symget('max_' || left(put(i, 2.))), best12.);
end;
run;
However, I'm getting the following error, which I don't understand. options mprint; shown. SAS appears to be interpreting scan as both an array and a variable, when it's a SAS function.
ERROR: Undeclared array referenced: scan.
MPRINT(OUTLIERS_MAX): if scan("var1 var2 var3 ... varN", i) > input(symget('max_'
|| left(put(i, 2.))), best12.) then scan("var1 var2 var3 ... varN", i) =
input(symget('max_' || left(put(i, 2.))), best12.);
ERROR: Variable scan has not been declared as an array.
MPRINT(OUTLIERS_MAX): end;
MPRINT(OUTLIERS_MAX): run;
Any help you can provide would be greatly appreciated.
The specific issue you have here is that you place SCAN on the left side of an equal sign. That is not allowed; SUBSTR is allowed to be used in this fashion, but not SCAN.