Hi,
I have a sample dataset for multiple imputation and I will use proc mianalyze.
I encounter two problems:
1. When visit 2 has no missing, the outcome of proc mianalyze does not show the p-values.
2. How can I get the adjusted p-values from proc mianalyze procedure.
DATA FORMI (keep=person gender y1-y4)
formixed(keep=person gender visit y);
input person gender$ y1-y4;
output FORMI;
datalines;
1 F 21.0 20.0 21.5 .
2 F 21.0 21.5 24.0 25.5
3 F 20.5 24.0 24.5 26.0
4 F 23.5 24.5 25.0 26.5
5 F 21.5 23.0 22.5 23.5
6 F 20.0 21.0 21.0 .
7 F 21.5 22.5 23.0 25.0
8 F 23.0 23.0 23.5 24.0
9 F 20.0 21.0 22.0 21.5
10 F 16.5 19.0 19.0 19.5
11 F 24.5 25.0 28.0 28.0
12 M 26.0 25.0 29.0 31.0
13 M 21.5 22.5 23.0 26.5
14 M 23.0 22.5 . 27.5
15 M 25.5 27.5 26.5 27.0
16 M 20.0 23.5 22.5 26.0
17 M 24.5 25.5 27.0 28.5
18 M 22.0 22.0 . 26.5
19 M 24.0 21.5 24.5 25.5
20 M 23.0 20.5 31.0 26.0
21 M 27.5 28.0 31.0 31.5
22 M 23.0 23.0 23.5 25.0
23 M 21.5 23.5 24.0 28.0
24 M 17.0 24.5 26.0 29.5
25 M 22.5 25.5 25.5 26.0
26 M 23.0 24.5 26.0 30.0
27 M 22.0 21.5 23.5 25.0
;
data formixed2;
set formixed;
by person;
if first.person then base = y;
base +0;
diff = y - base;
output;
run;
PROC MI DATA = FORMI OUT = MI1 SEED=21355417 NIMPUTE=10 ;
FCS ;
MNAR;
VAR Y1 Y2 Y3 Y4 ;
RUN;
DATA MI1;
SET MI1;
BVAL = Y1;
RUN;
PROC SORT DATA = MI1;
BY _IMPUTATION_ PERSON BVAL;
RUN;
PROC TRANSPOSE DATA = MI1 OUT = MIX1 NAME = VISIT ;
BY _IMPUTATION_ PERSON BVAL ;
VAR Y1 Y2 Y3 Y4 ;
RUN;
PROC MIXED DATA = MIX1;
BY _IMPUTATION_;
CLASS PERSON VISIT;
MODEL COL1 = BVAL VISIT;
REPEATED VISIT/TYPE =AR(1) SUBJECT = PERSON;
LSMEANS VISIT/PDIFF ADJUST = DUNNETT;
ODS OUTPUT DIFFS = DIFFS;
RUN;
PROC SORT DATA = DIFFS;
BY VISIT _IMPUTATION_;
RUN;
PROC MIANALYZE DATA = DIFFS ;
BY VISIT ;
MODELEFFECTS ESTIMATE;
STDERR STDERR;
ODS OUTPUT PARAMETERESTIMATES = PARAMETERESTIMATES;
RUN;
Moved to Procedures community.
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 25. Read more here about why you should contribute and what is in it for you!
Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.