topic lag function to estimate risk differences in New SAS User

lag function to estimate risk differences

Olivi — Wed, 25 Oct 2023 02:33:04 GMT

Hello everyone,

I am calculating risk differences with the lag function, I have a variable exposure category (with 3 exposure levels), I want to calculate the difference based on the reference category, but I have not succeeded, any suggestions?
help please

lag function to estimate risk differences

Olivi — Wed, 25 Oct 2023 02:44:41 GMT

Hello everyone, I am calculating risk differences with the lag function, I have a variable exposure category (with 3 exposure levels), I want to calculate the difference based on the reference category, but I have not succeeded, any suggestions? help please.

I am using this code, there is no problem for the difference between category 2 with the reference, but the calculation of the third category is no longer done with the reference, rather with the previous category (which I understand is what happens with the lag function) is there any way to set a reference category?

data test;
set test;
by time exposure;
rd = risk - lag(risk);
rr = risk / lag(risk);
if first.time then rd=.;
if first.time then rr=.;
run;

Re: lag function to estimate risk differences

Patrick — Wed, 25 Oct 2023 06:11:20 GMT

Please amend below HAVE sample data if it is not suitable for your problem.

Once you've created good enough sample data how should the desired result look like?

data have;
  infile datalines dsd truncover;
  input time exposure risk;
  datalines;
1,1,1
1,1,2
1,2,3
2,1,1
2,3,3
;

data want;
  set have;
  by time exposure;
  rd = risk - lag(risk);
  rr = risk / lag(risk);
  if first.time then call missing(rd,rr);
run;

proc print data=want;
run;

Re: lag function to estimate risk differences

Kurt_Bremser — Wed, 25 Oct 2023 06:12:00 GMT

What is the reference category?

Please also supply usable example data (in a working data step with datalines), and the expected result.

Re: lag function to estimate risk differences

Olivi — Thu, 26 Oct 2023 01:10:34 GMT

I will try, thank you

Re: lag function to estimate risk differences

Olivi — Thu, 26 Oct 2023 01:24:37 GMT

The exposure category has 3 values (0, 1 and 2) and the reference category is 0.

Example data:

data test;

input exposure time risk:

datalines;

0 0 0.01413

1 0 0.0125

2 0 0.1077

0 1 0.0491

1 1 0.0838

2 1 0.0678

;

I want to estimate the risk difference based on the reference category using the lag function.

Re: lag function to estimate risk differences

Patrick — Thu, 26 Oct 2023 01:53:38 GMT

Using your sample data how would the desired result look like? Providing such sample want data often helps a lot to clarify the requirements.

Not having such want data I'm not sure if I've got below formulas right - but the code should anyway give you the idea.

data test;
  input exposure time risk;
  datalines;
0 0 0.01413
1 0 0.0125
2 0 0.1077
0 1 0.0491
1 1 0.0838
2 1 0.0678
;

data want;
  set test;
  by time exposure;

  array risks {0:2} 8 _temporary_;

  risks[exposure]=risk;

  if last.time then
    do;
      rd = risks[0] - risks[1];
      rr = risks[0] / risks[2];
      output;
      call missing(of risks[*]);
    end;
  keep time rd rr;
run;

proc print data=want;
run;

Note: With a _temporary_ array the values get retained.

Re: lag function to estimate risk differences

Olivi — Thu, 26 Oct 2023 06:39:05 GMT

Thank you very much!