Flexible complex clinical demographics report
This will do any Major, Minor and Transposed data report.
You have Major and Minor nested headings.
This is a very old tip (2003?)
Can be substantially simplified, because the median is now available from 'proc sql'.
see for rtf report
https://dl.dropboxusercontent.com/u/15716238/utl_datnul.rtf
Style template at end of message.
You need to execute
%utl_rtflan100; * to build style;
You can know get the median using sql, which cuts out 3 steps;
HAVE
====
Up to 40 obs from dm total obs=91
Obs TRT PAT WGT HGT RCD AGE SEX
1 Aspirin 1 77.1 138.78 1 50 2
2 Aspirin 50 76.2 137.16 1 49 2
3 Placebo 2 71.4 128.52 1 58 2
4 Placebo 51 112.0 201.60 1 67 2
5 Aspirin 3 56.0 100.80 1 61 2
6 Placebo 52 84.4 151.92 1 61 2
7 Aspirin 4 76.2 137.16 1 38 2
8 Aspirin 53 70.3 126.54 1 64 2
9 Aspirin 5 88.9 160.02 1 54 2
....
87 Placebo 45 59.5 107.10 1 59 2
88 Placebo 48 62.6 112.68 1 44 2
89 Placebo 46 40.8 73.44 1 55 2
90 Placebo 49 74.4 133.92 1 60 2
91 Aspirin 47 64.2 115.56 1 55 2
LAYOUT OF REPORT
================
SEX
a. First page
b. First two rows
c. Major heading Sex n (%)
d. minor heading Male/Female
value sex
1 ='SEX @Page @01 @Order @010 @Sex - n (%) @\li360 Male'
2 = 'SEX @Page @01 @Order @020 @Sex - n (%) @\li360 Female';
proc format;
value sex
1 ='SEX @Page @01 @Order @010 @Sex - n (%) @\li360 Male'
2 = 'SEX @Page @01 @Order @020 @Sex - n (%) @\li360 Female';
value rcd
1 = "RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian"
2 = "RCD @Page @01 @Order @050 @Race - n (%) @\li360 Black or African American"
3 = "RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino"
4 = "RCD @Page @01 @Order @070 @Race - n (%) @\li360 Asian"
5 = "RCD @Page @01 @Order @080 @Race - n (%) @\li360 Japanese"
6 = "RCD @Page @01 @Order @090 @Race - n (%) @\li360 American Indian or Alaska Native"
7 = "RCD @Page @01 @Order @100 @Race - n (%) @\li360 Native Hawaiian or Other Pacific Islander"
88 = "RCD @Page @01 @Order @110 @Race - n (%) @\li360 Other";
value rcx
2, 3, 4, 5, 6, 7, 88
= "RCX @Page @01 @Order @022 @Race - n (%) @\li360 Non-White or Caucasian"
1 = "RCX @Page @XX @Order @0XX @Race - n (%) @\li360 White Caucasian"; /* not in report */
value age_n
1 = "AGE @Page @02 @Order @010 @Age @\li360 N" @N
2 = "AGE @Page @02 @Order @020 @Age @\li360 Mean(SD)" @MEAN STD
3 = "AGE @Page @02 @Order @030 @Age @\li360 Median" @MEDIAN
4 = "AGE @Page @02 @Order @040 @Age @\li360 Min, Max" @MIN MAX ; /* 8th item means univariate stat */
value wgt_n
1 = "WGT @Page @02 @Order @050 @Weight @\li360 N" @N
2 = "WGT @Page @02 @Order @060 @Weight @\li360 Mean(SD)" @MEAN STD
3 = "WGT @Page @02 @Order @070 @Weight @\li360 Median" @MEDIAN
4 = "WGT @Page @02 @Order @080 @Weight @\li360 Min, Max" @MIN MAX ;
value hgt_n
1 = "HGT @Page @02 @Order @090 @Height @\li360 N" @N
2 = "HGT @Page @02 @Order @100 @Height @\li360 Mean(SD)" @MEAN STD
3 = "HGT @Page @02 @Order @110 @Height @\li360 Median" @MEDIAN
4 = "HGT @Page @02 @Order @120 @Height @\li360 Min, Max" @MIN MAX ;
/* expects all variables to have the same stats*/
/* but can be generalized */
run;
WANT
====
see for rtf report
https://dl.dropboxusercontent.com/u/15716238/utl_datnul.rtf
Text version
PAGE 1
Table : Demographics
(Intent to Treat Population)
Aspirin Placebo All
(N= 45) (N= 46) (N= 91)
Sex - n (%)
Male 9(20%) 12(26%) 21(23%)
Female 36(80%) 34(74%) 70(77%)
Race - n (%)
Non-White or Caucasian 11(24%) 5(11%) 16(18%)
White or Caucasian 34(76%) 41(89%) 75(82%)
Black or African American 3(7%) 4(9%) 7(8%)
Hispanic or Latino 5(11%) 1(2%) 6(7%)
Asian 2(4%) 0(0%) 2(2%)
Japanese 0(0%) 0(0%) 0(0%)
American Indian or Alaska Native 0(0%) 0(0%) 0(0%)
Native Hawaiian or Other Pacific Islander 0(0%) 0(0%) 0(0%)
Other 1(2%) 0(0%) 1(1%)
Page 1 of 2
Program: c:/utl/dm.sas_09FEB17
Log: c:/utl/dm.log_09FEB17
see Protocol 1013.6(Oncology)
PAGE 2
Table : Demographics
(Intent to Treat Population)
Aspirin Placebo All
(N= 45) (N= 46) (N= 91)
Age
N 45 46 91
Mean(SD) 52(8.6) 51(9.6) 51(9.1)
Median 31, 68 26, 71 26, 71
Weight
N 45 46 91
Mean(SD) 74(15.2) 78(19.7) 76(17.7)
Median 49, 125 41, 120 41, 125
Height
N 45 46 91
Mean(SD) 133(27.3 141(35.5) 137(31.8)
Median 88, 224 73, 216 73, 224
Page 2 of 2
Program: c:/utl/dm.sas_09FEB17
Log: c:/utl/dm.log_09FEB17
see Protocol 1013.6(Oncology)
*
____ _ _ _
/ ___| ___ | |_ _| |_(_) ___ _ __
\___ \ / _ \| | | | | __| |/ _ \| '_ \
___) | (_) | | |_| | |_| | (_) | | | |
|____/ \___/|_|\__,_|\__|_|\___/|_| |_|
;
/* T002600 LATEST ATTEMPT TO CREATE COMPLEX REPORT WITH MINIMAL LINES OF CODE 10/7/2001 */
%let output1=d:/rtf/utl_datnul.rtf;
options validvarname=upcase; /* will not work without this */
proc sql;
Create table dm(pat float, wgt float, hgt float, rcd float, trt varchar(8), age float, sex float);
Insert into dm(pat, wgt, hgt, rcd, trt, age, sex)
Values(1, 77.1, 138.78, 1, "Aspirin" 50, 2) Values(50, 76.2, 137.16, 1, "Aspirin" 49, 2)
Values(2, 71.4, 128.52, 1, "Placebo" 58, 2) Values(51, 112.0, 201.60, 1, "Placebo" 67, 2)
Values(3, 56.0, 100.80, 1, "Aspirin" 61, 2) Values(52, 84.4, 151.92, 1, "Placebo" 61, 2)
Values(4, 76.2, 137.16, 1, "Aspirin" 38, 2) Values(53, 70.3, 126.54, 1, "Aspirin" 64, 2)
Values(5, 88.9, 160.02, 1, "Aspirin" 54, 2) Values(54, 87.1, 156.78, 2, "Placebo" 54, 2)
Values(6, 119.8, 215.64, 2, "Placebo" 50, 2) Values(55, 89.4, 160.92, 1, "Placebo" 49, 2)
Values(7, 66.7, 120.06, 1, "Placebo" 43, 2) Values(56, 88.5, 159.30, 1, "Aspirin" 56, 2)
Values(8, 111.6, 200.88, 1, "Placebo" 66, 2) Values(57, 67.5, 121.50, 1, "Placebo" 42, 2)
Values(9, 67.4, 121.32, 1, "Placebo" 47, 2) Values(58, 102.5, 184.50, 1, "Placebo" 48, 2)
Values(10, 92.1, 165.78, 1, "Placebo" 59, 2) Values(59, 81.1, 145.98, 1, "Placebo" 53, 2)
Values(11, 102.1, 183.78, 1, "Aspirin" 56, 2) Values(60, 72.6, 130.68, 1, "Aspirin" 59, 2)
Values(12, 66.2, 119.16, 1, "Placebo" 45, 2) Values(61, 124.5, 224.10, 1, "Aspirin" 47, 2)
Values(13, 112.5, 202.50, 2, "Placebo" 57, 2) Values(62, 70.0, 126.00, 1, "Placebo" 43, 2)
Values(14, 103.9, 187.02, 2, "Aspirin" 47, 2) Values(63, 62.6, 112.68, 3, "Aspirin" 53, 2)
Values(15, 70.8, 127.44, 1, "Placebo" 56, 2) Values(64, 60.8, 109.44, 4, "Aspirin" 50, 2)
Values(17, 79.8, 143.64, 1, "Aspirin" 68, 2) Values(65, 58.7, 105.66, 1, "Placebo" 47, 2)
Values(18, 65.1, 117.18, 1, "Placebo" 35, 2) Values(66, 63.7, 114.66, 1, "Aspirin" 43, 2)
Values(19, 100.7, 181.26, 1, "Placebo" 45, 2) Values(67, 77.1, 138.78, 88, "Aspirin" 49, 2)
Values(20, 61.7, 111.06, 1, "Aspirin" 54, 1) Values(68, 53.5, 96.30, 1, "Placebo" 49, 2)
Values(21, 79.2, 142.56, 2, "Placebo" 50, 1) Values(69, 95.7, 172.26, 1, "Aspirin" 55, 2)
Values(22, 89.8, 161.64, 1, "Placebo" 54, 1) Values(70, 68.0, 122.40, 3, "Aspirin" 57, 2)
Values(23, 63.1, 113.58, 2, "Aspirin" 38, 1) Values(71, 54.0, 97.20, 3, "Aspirin" 66, 2)
Values(24, 67.8, 122.04, 1, "Placebo" 57, 1) Values(72, 85.3, 153.54, 3, "Aspirin" 44, 2)
Values(25, 82.6, 148.68, 1, "Aspirin" 53, 1) Values(74, 52.2, 93.96, 1, "Aspirin" 55, 2)
Values(26, 90.7, 163.26, 1, "Placebo" 38, 1) Values(75, 86.2, 155.16, 1, "Aspirin" 58, 2)
Values(27, 73.0, 131.40, 1, "Aspirin" 60, 1) Values(76, 59.0, 106.20, 3, "Placebo" 46, 2)
Values(28, 64.4, 115.92, 1, "Placebo" 38, 1) Values(77, 59.0, 106.20, 4, "Aspirin" 45, 2)
Values(29, 59.4, 106.92, 1, "Placebo" 51, 1) Values(78, 116.6, 209.88, 1, "Placebo" 51, 2)
Values(30, 70.8, 127.44, 1, "Aspirin" 61, 1) Values(79, 55.1, 99.18, 1, "Placebo" 39, 2)
Values(31, 72.1, 129.78, 1, "Aspirin" 56, 1) Values(80, 64.9, 116.82, 1, "Aspirin" 40, 2)
Values(32, 54.0, 97.20, 1, "Aspirin" 56, 1) Values(81, 85.3, 153.54, 1, "Aspirin" 53, 2)
Values(33, 62.8, 113.04, 1, "Aspirin" 37, 1) Values(82, 45.8, 82.44, 1, "Placebo" 57, 2)
Values(34, 62.6, 112.68, 1, "Placebo" 37, 1) Values(83, 71.7, 129.06, 2, "Aspirin" 52, 2)
Values(35, 79.4, 142.92, 1, "Placebo" 44, 1) Values(84, 61.9, 111.42, 1, "Aspirin" 34, 2)
Values(36, 60.8, 109.44, 1, "Placebo" 50, 1) Values(85, 82.1, 147.78, 1, "Aspirin" 46, 2)
Values(37, 89.8, 161.64, 3, "Aspirin" 50, 1) Values(86, 58.5, 105.30, 1, "Aspirin" 53, 2)
Values(38, 76.8, 138.24, 1, "Placebo" 40, 1) Values(87, 68.9, 124.02, 1, "Aspirin" 66, 2)
Values(39, 87.1, 156.78, 1, "Placebo" 51, 1) Values(88, 68.9, 124.02, 1, "Aspirin" 42, 2)
Values(40, 64.3, 115.74, 1, "Placebo" 26, 1) Values(89, 104.8, 188.64, 1, "Placebo" 69, 2)
Values(41, 109.0, 196.20, 1, "Placebo" 58, 2) Values(90, 79.4, 142.92, 1, "Placebo" 65, 2)
Values(42, 77.2, 138.96, 1, "Placebo" 44, 2) Values(91, 87.1, 156.78, 1, "Aspirin" 58, 2)
Values(43, 78.0, 140.40, 1, "Aspirin" 57, 2) Values(92, 89.8, 161.64, 1, "Placebo" 71, 2)
Values(44, 49.0, 88.20, 1, "Aspirin" 31, 2) Values(93, 75.3, 135.54, 1, "Aspirin" 52, 2)
Values(45, 59.5, 107.10, 1, "Placebo" 59, 2) Values(48, 62.6, 112.68, 1, "Placebo" 44, 2)
Values(46, 40.8, 73.44, 1, "Placebo" 55, 2) Values(49, 74.4, 133.92, 1, "Placebo" 60, 2)
Values(47, 64.2, 115.56, 1, "Aspirin" 55, 2)
;quit;
proc print width=min;
run;quit;
/* report layout */
/* need formats because not all levels are in the data
'SEX@Page @01 @Order @01 @Sex - n (%) @\li360 Male'
SEX variable and format for variable
Page 1 of reprt
Order 1 first lne on page 1
Sex - n(%) Major Heading
Male- Minor heading
formats that end in _n are univariate stats -> mean(sd)
8th items on univariate variables are the requires stats
*/
/* cannot have formats prior to this code - could backup and restore */
proc datasets library=work mt=catalog;
delete formats;
run;quit;
/* this method does require that you layout the entire report - see non format method for work around */
/* it might be better in the future to add a treatment format - even though it is not needed */
proc format;
value sex
1 ='SEX @Page @01 @Order @010 @Sex - n (%) @\li360 Male'
2 = 'SEX @Page @01 @Order @020 @Sex - n (%) @\li360 Female';
value rcd
1 = "RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian"
2 = "RCD @Page @01 @Order @050 @Race - n (%) @\li360 Black or African American"
3 = "RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino"
4 = "RCD @Page @01 @Order @070 @Race - n (%) @\li360 Asian"
5 = "RCD @Page @01 @Order @080 @Race - n (%) @\li360 Japanese"
6 = "RCD @Page @01 @Order @090 @Race - n (%) @\li360 American Indian or Alaska Native"
7 = "RCD @Page @01 @Order @100 @Race - n (%) @\li360 Native Hawaiian or Other Pacific Islander"
88 = "RCD @Page @01 @Order @110 @Race - n (%) @\li360 Other";
value rcx
2, 3, 4, 5, 6, 7, 88
= "RCX @Page @01 @Order @022 @Race - n (%) @\li360 Non-White or Caucasian"
1 = "RCX @Page @XX @Order @0XX @Race - n (%) @\li360 White Caucasian"; /* not in report */
value age_n
1 = "AGE @Page @02 @Order @010 @Age @\li360 N" @N
2 = "AGE @Page @02 @Order @020 @Age @\li360 Mean(SD)" @MEAN STD
3 = "AGE @Page @02 @Order @030 @Age @\li360 Median" @MEDIAN
4 = "AGE @Page @02 @Order @040 @Age @\li360 Min, Max" @MIN MAX ; /* 8th item means univariate stat */
value wgt_n
1 = "WGT @Page @02 @Order @050 @Weight @\li360 N" @N
2 = "WGT @Page @02 @Order @060 @Weight @\li360 Mean(SD)" @MEAN STD
3 = "WGT @Page @02 @Order @070 @Weight @\li360 Median" @MEDIAN
4 = "WGT @Page @02 @Order @080 @Weight @\li360 Min, Max" @MIN MAX ;
value hgt_n
1 = "HGT @Page @02 @Order @090 @Height @\li360 N" @N
2 = "HGT @Page @02 @Order @100 @Height @\li360 Mean(SD)" @MEAN STD
3 = "HGT @Page @02 @Order @110 @Height @\li360 Median" @MEDIAN
4 = "HGT @Page @02 @Order @120 @Height @\li360 Min, Max" @MIN MAX ;
/* expects all variables to have the same stats*/
/* but can be generalized */
run;
/* put the layout into a sas table */
proc format library=work.formats cntlout=unv1st;
run;
/* normalize the data */
/* you could generate this data step from the format - I choose to KISS */
data nrm1st;
keep trt question answer;
length question $96;
set dm;
question=put(sex,sex.); answer=1; link all;
question=put(rcd,rcd.); answer=1; link all;
question=put(rcd,rcx.); answer=1; link all;
question='AGE' ; answer=age; link all;
question='WGT' ; answer=wgt; link all;
question='HGT' ; answer=hgt; link all;
return;
all:
output;
savtrt=trt;
trt="All";
output;
trt=savtrt;
return;
run;
/*
Up to 40 obs WORK.NRM1ST total obs=1,092
Obs QUESTION TRT ANSWER
1 SEX @Page @01 @Order @020 @Sex - n (%) @\li360 Female Aspirin 1
2 SEX @Page @01 @Order @020 @Sex - n (%) @\li360 Female All 1
3 RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian Aspirin 1
4 RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian All 1
5 RCX @Page @XX @Order @0XX @Race - n (%) @\li360 White Caucasian Aspirin 1
6 RCX @Page @XX @Order @0XX @Race - n (%) @\li360 White Caucasian All 1
7 AGE Aspirin 50
8 AGE All 50
9 WGT Aspirin 77.1
10 WGT All 77.1
11 HGT Aspirin 138.78
12 HGT All 138.78
*/
/* need the shell so missing categories can be represented in the report */
/* note we use the format to generate all combinations */
/* answer will be the weights missing categories will have 0 counts and percents */
data shl;
length question $96;
keep trt question answer;
set unv1st(where=(scan(label,8,'@') eq '')); /* only categorical variables */
trt="Placebo"; question=label; answer=0; output;
trt="Aspirin"; question=label; answer=0; output;
trt="All" ; question=label; answer=0; output;
run;
/*
Up to 40 obs WORK.SHL total obs=54
Obs QUESTION TRT ANSWER
1 RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian Placebo 0
2 RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian Aspirin 0
3 RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian All 0
4 RCD @Page @01 @Order @050 @Race - n (%) @\li360 Black or African American Placebo 0
5 RCD @Page @01 @Order @050 @Race - n (%) @\li360 Black or African American Aspirin 0
6 RCD @Page @01 @Order @050 @Race - n (%) @\li360 Black or African American All 0
*/
/* fill in the missing categories with 0 answers(weights) */
proc sql;
create
table shldat as
select
coalesce(dat.trt,shl.trt) as trt
,coalesce(substr(dat.question,1,3),substr(shl.question,1,3)) as grp length=3
,coalesce(dat.question,shl.question) as question
,coalesce(dat.answer,shl.answer) as answer
from
(select distinct * from shl) as shl left join nrm1st as dat
on
shl.question = dat.question and
shl.trt = dat.trt
order
by grp, trt, question;
;quit;
/*
All Obs(560) from dataset shldat
Weights
Obs TRT GRP QUESTION ANSWER
133 Aspirin RCD RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino 1
134 Aspirin RCD RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino 1
135 Aspirin RCD RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino 1
136 Aspirin RCD RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino 1
137 Aspirin RCD RCD @Page @01 @Order @070 @Race - n (%) @\li360 Asian 1
138 Aspirin RCD RCD @Page @01 @Order @070 @Race - n (%) @\li360 Asian 1
139 Aspirin RCD RCD @Page @01 @Order @080 @Race - n (%) @\li360 Japanese 0 Not in data
140 Aspirin RCD RCD @Page @01 @Order @090 @Race - n (%) @\li360 American Indian or Alaska Native 0 Not in data
141 Aspirin RCD RCD @Page @01 @Order @100 @Race - n (%) @\li360 Native Hawaiian or Other Pacific Islander 0
142 Aspirin RCD RCD @Page @01 @Order @110 @Race - n (%) @\li360 Other 1
*/
/* categorical n(pct) variables */
proc sql;
create
table cntpct as
select
distinct
l.trt
,l.grp
,l.question
,r.sumgrp
,cats(put(sum(l.answer),4.),'(',put(sum(l.answer)/r.sumgrp,percent.),')') as answer
from
shldat as l, (select trt, grp, sum(answer) as sumgrp from shldat group by trt, grp) as r
where
l.trt = r.trt and
l.grp = r.grp
group
by l.trt, l.grp, l.question
;quit;
/*
Up to 40 obs WORK.CNTPCT total obs=36
Obs TRT GRP QUESTION SUMGRP ANSWER
1 All RCD RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian 91 75(82%)
2 All RCD RCD @Page @01 @Order @050 @Race - n (%) @\li360 Black or African American 91 7(8%)
3 All RCD RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino 91 6(7%)
4 All RCD RCD @Page @01 @Order @070 @Race - n (%) @\li360 Asian 91 2(2%)
5 All RCD RCD @Page @01 @Order @080 @Race - n (%) @\li360 Japanese 91 0(0%)
6 All RCD RCD @Page @01 @Order @090 @Race - n (%) @\li360 American Indian or Alaska Native 91 0(0%)
7 All RCD RCD @Page @01 @Order @100 @Race - n (%) @\li360 Native Hawaiian or Other Pacific Islander 91 0(0%)
8 All RCD RCD @Page @01 @Order @110 @Race - n (%) @\li360 Other 91 1(1%)
9 All RCX RCX @Page @01 @Order @022 @Race - n (%) @\li360 Non-White or Caucasian 91 16(18%)
10 All RCX RCX @Page @XX @Order @0XX @Race - n (%) @\li360 White Caucasian 91 75(82%)
11 All SEX SEX @Page @01 @Order @010 @Sex - n (%) @\li360 Male 91 0(0%)
12 All SEX SEX @Page @01 @Order @020 @Sex - n (%) @\li360 Female 91 91(100%)
13 Aspirin RCD RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian 45 34(76%)
14 Aspirin RCD RCD @Page @01 @Order @050 @Race - n (%) @\li360 Black or African American 45 3(7%)
15 Aspirin RCD RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino 45 5(11%)
16 Aspirin RCD RCD @Page @01 @Order @070 @Race - n (%) @\li360 Asian 45 2(4%)
*/
/* lets get the statistics we need from the format */
proc sql;
select distinct(scan(label,8,'@')) into :unvanl separated by ' ' from unv1st where index(fmtname,'_N')>0;
select distinct(quote(strip(scan(label,1,'@')))) into :unvvar separated by ' ' from unv1st where index(fmtname,'_N')>0;
quit;
%put &=unvanl;
%put &=unvvar;
/*
UNVANL=MEAN STD MEDIAN MIN MAX N
UNVVAR="AGE" "HGT" "WGT"
*/
ods output summary=demunv;
proc means data=nrm1st(where=(scan(question,1,'@') in (&unvvar))) &unvanl nway;
format question $3.;
class trt question;
var answer;
run;
ods output close;
/*
Up to 40 obs from demunv total obs=9
ANSWER_ ANSWER_
Obs TRT QUESTION NOBS ANSWER_MEAN STDDEV MEDIAN ANSWER_MIN ANSWER_MAX ANSWER_N
1 All AGE 91 51.164835165 9.0740946733 52 26 71 91
2 All HGT 91 137.14021978 31.816178344 130.68 73.44 224.1 91
3 All WGT 91 76.189010989 17.675654635 72.6 40.8 124.5 91
4 Aspirin AGE 45 51.733333333 8.5610109853 53 31 68 45
5 Aspirin HGT 45 133.056 27.306971338 129.78 88.2 224.1 45
6 Aspirin WGT 45 73.92 15.170539632 72.1 49 124.5 45
7 Placebo AGE 46 50.608695652 9.6112856369 50 26 71 46
8 Placebo HGT 46 141.13565217 35.530819151 136.08 73.44 215.64 46
9 Placebo WGT 46 78.408695652 19.739343973 75.6 40.8 119.8 46
*/
* normalize;
data nrmunv;
keep trt grp question answer;
length question answer $96;
do until (dne);
set demunv end=dne;
format _all_;
grp=question;
fmt=strip(question)!!'_n';
question=putn(1,fmt);
answer=put(answer_n,5.);
output;
question=putn(2,fmt);
answer=cats(put(answer_mean,??5.),'(',put(answer_stddev,??5.1),')');
output;
question=putn(3,fmt);
answer=strip(put(answer_min,5.))!!', '!!strip(put(answer_max,5.));
output;
end;
do until (dn1);
set cntpct end=dn1;
format _all_;
output;
end;
stop;
run;
/*
Obs QUESTION ANSWER TRT GRP
1 AGE @Page @02 @Order @010 @Age @\li360 N @N 91 All AGE
2 AGE @Page @02 @Order @020 @Age @\li360 Mean(SD) @MEAN STD 51(9.1) All AGE
3 AGE @Page @02 @Order @030 @Age @\li360 Median @MEDIAN 26, 71 All AGE
4 HGT @Page @02 @Order @090 @Height @\li360 N @N 91 All HGT
5 HGT @Page @02 @Order @100 @Height @\li360 Mean(SD) @MEAN STD 137(31.8) All HGT
6 HGT @Page @02 @Order @110 @Height @\li360 Median @MEDIAN 73, 224 All HGT
7 WGT @Page @02 @Order @050 @Weight @\li360 N @N 91 All WGT
8 WGT @Page @02 @Order @060 @Weight @\li360 Mean(SD) @MEAN STD 76(17.7) All WGT
9 WGT @Page @02 @Order @070 @Weight @\li360 Median @MEDIAN 41, 125 All WGT
28 RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian 75(82%) All RCD
29 RCD @Page @01 @Order @050 @Race - n (%) @\li360 Black or African American 7(8%) All RCD
30 RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino 6(7%) All RCD
31 RCD @Page @01 @Order @070 @Race - n (%) @\li360 Asian 2(2%) All RCD
32 RCD @Page @01 @Order @080 @Race - n (%) @\li360 Japanese 0(0%) All RCD
33 RCD @Page @01 @Order @090 @Race - n (%) @\li360 American Indian or Alaska Native 0(0%) All RCD
34 RCD @Page @01 @Order @100 @Race - n (%) @\li360 Native Hawaiian or Other Pacific Islander 0(0%) All RCD
38 SEX @Page @01 @Order @010 @Sex - n (%) @\li360 Male 21(23%) All SEX
39 SEX @Page @01 @Order @020 @Sex - n (%) @\li360 Female 70(77%) All SEX
proc sort data=nrmunv out=srt nodupkey;
by question trt;
run;
proc transpose data=srt out=xpo(drop=_name_) ;
by question;
id trt;
var answer;
run;
/*
proc print width=min;
run;quit;
Obs QUESTION ALL ASPIRIN PLACEBO
1 AGE @Page @02 @Order @010 @Age @\li360 N @N 91 45 46
2 AGE @Page @02 @Order @020 @Age @\li360 Mean(SD) @MEAN STD 51(9.1) 52(8.6) 51(9.6)
3 AGE @Page @02 @Order @030 @Age @\li360 Median @MEDIAN 26, 71 31, 68 26, 71
4 HGT @Page @02 @Order @090 @Height @\li360 N @N 91 45 46
5 HGT @Page @02 @Order @100 @Height @\li360 Mean(SD) @MEAN STD 137(31.8) 133(27.3) 141(35.5)
6 HGT @Page @02 @Order @110 @Height @\li360 Median @MEDIAN 73, 224 88, 224 73, 216
7 RCD @Page @01 @Order @030 @Race - n (%) @\li360 White or Caucasian 75(82%) 34(76%) 41(89%)
8 RCD @Page @01 @Order @050 @Race - n (%) @\li360 Black or African American 7(8%) 3(7%) 4(9%)
9 RCD @Page @01 @Order @060 @Race - n (%) @\li360 Hispanic or Latino 6(7%) 5(11%) 1(2%)
10 RCD @Page @01 @Order @070 @Race - n (%) @\li360 Asian 2(2%) 2(4%) 0(0%)
11 RCD @Page @01 @Order @080 @Race - n (%) @\li360 Japanese 0(0%) 0(0%) 0(0%)
12 RCD @Page @01 @Order @090 @Race - n (%) @\li360 American Indian or Alaska Native 0(0%) 0(0%) 0(0%)
13 RCD @Page @01 @Order @100 @Race - n (%) @\li360 Native Hawaiian or Other Pacific Islander 0(0%) 0(0%) 0(0%)
14 RCD @Page @01 @Order @110 @Race - n (%) @\li360 Other 1(1%) 1(2%) 0(0%)
15 RCX @Page @01 @Order @022 @Race - n (%) @\li360 Non-White or Caucasian 16(18%) 11(24%) 5(11%)
16 RCX @Page @XX @Order @0XX @Race - n (%) @\li360 White Caucasian 75(82%) 34(76%) 41(89%)
17 SEX @Page @01 @Order @010 @Sex - n (%) @\li360 Male 21(23%) 9(20%) 12(26%)
18 SEX @Page @01 @Order @020 @Sex - n (%) @\li360 Female 70(77%) 36(80%) 34(74%)
19 WGT @Page @02 @Order @050 @Weight @\li360 N @N 91 45 46
20 WGT @Page @02 @Order @060 @Weight @\li360 Mean(SD) @MEAN STD 76(17.7) 74(15.2) 78(19.7)
21 WGT @Page @02 @Order @070 @Weight @\li360 Median @MEDIAN 41, 125 49, 125 41, 120
*/
proc sql;
create
table prerpt as
select
input(scan(question,3,'@'),5.) as pge
,scan(question,5,'@') as odr length=3
,scan(question,6,'@') as mjr length=64
,scan(question,7,'@') as mnr length=64
,aspirin length=24
,placebo length=24
,all length=24
from
xpo
where
scan(question,5,'@') ne 'XX'
order
by pge, odr
;quit;
proc sql;select max(pge) into :maxpge separated by '' from prerpt;quit;
%put &=maxpge;
/* MAXPGE=2 */
/* lets get big N's */
proc sql;
select resolve('%Let '!!trt!!'=%sysfunc(compbl('!!trt!!'#(N='!!Put(Count(answer),4.)!!');))')
from nrm1st where question='AGE' Group by Trt
;quit;
%put &=all;
%put &=aspirin;
%put &=placebo;
/*
ALL=All #(N= 91)
ASPIRIN=Aspirin #(N= 45)
PLACEBO=Placebo #(N= 46)
%put &=sysdate;
*/
%let ttl1=Table : Demographics;
%let TTL2=Safety Dataset;
%let TTL3=(Intent to Treat Population);
%let TTL4=Placebo-Aspirin;
/*
%put &=ttl1;
%utl_rtflan100;
options nodate nonumber orientation=portrait;
title;footnote;
ods escapechar='^';
ods listing close;
ods rtf file="&output1" style=utl_rtflan100 notoc_data;
%macro mny(pgemax);
%do pge=1 %to &pgemax;
ods rtf prepage="^S={outputwidth=100% just=c font_size=11pt font_face=arial} {&ttl1}^{newline}{&ttl3}";
proc report data=prerpt (where=(pge=&pge)) nowd split='#' missing;
cols mjr mnr aspirin placebo all;
define mjr / order noprint order=data;
define mnr / display "" style={cellwidth=30% just=l } order=data;
define aspirin / display "&aspirin" style={cellwidth=22% just=c } order=data;
define placebo / display "&placebo" style={cellwidth=22% just=c } order=data;
define All / display "&All" style={cellwidth=23% just=c } order=data;
compute before mjr / style=[just=l];
line mjr $96.;
endcomp;
run;quit;
ods rtf text="^S={outputwidth=100% just=r font_size=9pt} Page &pge of &pgemax";
ods rtf text="^S={outputwidth=100% just=l font_size=8pt font_style=italic} {Program: c:/utl/dm.sas_&sysdate}";
ods rtf text="^S={outputwidth=100% just=l font_size=8pt font_style=italic} {Log: c:/utl/dm.log_&sysdate}";
ods rtf text="^S={outputwidth=100% just=l font_size=8pt font_style=italic} {see Protocol 1013.6(Oncology)}";
run;quit;
%end;
%mend mny;
%mny(&maxpge);
ods rtf close;
ods listing;
/*
PAGE 1
Table : Demographics
(Intent to Treat Population)
Aspirin Placebo All
(N= 45) (N= 46) (N= 91)
Sex - n (%)
Male 9(20%) 12(26%) 21(23%)
Female 36(80%) 34(74%) 70(77%)
Race - n (%)
Non-White or Caucasian 11(24%) 5(11%) 16(18%)
White or Caucasian 34(76%) 41(89%) 75(82%)
Black or African American 3(7%) 4(9%) 7(8%)
Hispanic or Latino 5(11%) 1(2%) 6(7%)
Asian 2(4%) 0(0%) 2(2%)
Japanese 0(0%) 0(0%) 0(0%)
American Indian or Alaska Native 0(0%) 0(0%) 0(0%)
Native Hawaiian or Other Pacific Islander 0(0%) 0(0%) 0(0%)
Other 1(2%) 0(0%) 1(1%)
Page 1 of 2
Program: c:/utl/dm.sas_09FEB17
Log: c:/utl/dm.log_09FEB17
see Protocol 1013.6(Oncology)
PAGE 2
Table : Demographics
(Intent to Treat Population)
Aspirin Placebo All
(N= 45) (N= 46) (N= 91)
Age
N 45 46 91
Mean(SD) 52(8.6) 51(9.6) 51(9.1)
Median 31, 68 26, 71 26, 71
Weight
N 45 46 91
Mean(SD) 74(15.2) 78(19.7) 76(17.7)
Median 49, 125 41, 120 41, 125
Height
N 45 46 91
Mean(SD) 133(27.3 141(35.5) 137(31.8)
Median 88, 224 73, 216 73, 224
Page 2 of 2
Program: c:/utl/dm.sas_09FEB17
Log: c:/utl/dm.log_09FEB17
see Protocol 1013.6(Oncology)
*____ _______ ___ _____
/ ___|_ _\ \ / / | | ____|
\___ \ | | \ V /| | | _|
___) || | | | | |___| |___
|____/ |_| |_| |_____|_____|
;
%Macro utl_rtflan100
(
style=utl_rtflan100,
frame=box,
rules=groups,
bottommargin=1.0in,
topmargin=1.5in,
rightmargin=1.0in,
cellheight=10pt,
cellpadding = 7,
cellspacing = 3,
leftmargin=.75in,
borderwidth = 1
) / Des="SAS Rtf Template for CompuCraft";
options orientation=landscape;run;quit;
ods path work.templat(update) sasuser.templat(update) sashelp.tmplmst(read);
Proc Template;
define style &Style;
parent=styles.rtf;
replace body from Document /
protectspecialchars=off
asis=on
bottommargin=&bottommargin
topmargin =&topmargin
rightmargin =&rightmargin
leftmargin =&leftmargin
;
replace color_list /
'link' = blue
'bgH' = _undef_
'fg' = black
'bg' = _undef_;
replace fonts /
'TitleFont2' = ("Arial, Helvetica, Helv",11pt,Bold)
'TitleFont' = ("Arial, Helvetica, Helv",11pt,Bold)
'HeadingFont' = ("Arial, Helvetica, Helv",10pt)
'HeadingEmphasisFont' = ("Arial, Helvetica, Helv",10pt,Italic)
'StrongFont' = ("Arial, Helvetica, Helv",10pt,Bold)
'EmphasisFont' = ("Arial, Helvetica, Helv",10pt,Italic)
'FixedFont' = ("Courier New, Courier",9pt)
'FixedEmphasisFont' = ("Courier New, Courier",9pt,Italic)
'FixedStrongFont' = ("Courier New, Courier",9pt,Bold)
'FixedHeadingFont' = ("Courier New, Courier",9pt,Bold)
'BatchFixedFont' = ("Courier New, Courier",7pt)
'docFont' = ("Arial, Helvetica, Helv",10pt)
'FootFont' = ("Arial, Helvetica, Helv", 9pt)
'StrongFootFont' = ("Arial, Helvetica, Helv",8pt,Bold)
'EmphasisFootFont' = ("Arial, Helvetica, Helv",8pt,Italic)
'FixedFootFont' = ("Courier New, Courier",8pt)
'FixedEmphasisFootFont'= ("Courier New, Courier",8pt,Italic)
'FixedStrongFootFont' = ("Courier New, Courier",7pt,Bold);
replace GraphFonts /
'GraphDataFont' = ("Arial, Helvetica, Helv",8pt)
'GraphAnnoFont' = ("Arial, Helvetica, Helv",8pt)
'GraphValueFont' = ("Arial, Helvetica, Helv",10pt)
'GraphUnicodeFont' = ("Arial, Helvetica, Helv",10pt)
'GraphLabelFont' = ("Arial, Helvetica, Helv",10pt,Bold)
'GraphLabel2Font' = ("Arial, Helvetica, Helv",10pt,Bold)
'GraphFootnoteFont' = ("Arial, Helvetica, Helv",8pt)
'GraphTitle1Font' = ("Arial, Helvetica, Helv",11pt,Bold)
'GraphTitleFont' = ("Arial, Helvetica, Helv",11pt,Bold);
style table from table /
outputwidth=100%
protectspecialchars=off
asis=on
background = colors('tablebg')
frame=&frame
rules=&rules
cellheight = &cellheight
cellpadding = &cellpadding
cellspacing = &cellspacing
bordercolor = colors('tableborder')
borderwidth = &borderwidth;
replace Footer from HeadersAndFooters
/ font = fonts('FootFont') just=left asis=on protectspecialchars=off ;
replace FooterFixed from Footer
/ font = fonts('FixedFootFont') just=left asis=on protectspecialchars=off;
replace FooterEmpty from Footer
/ font = fonts('FootFont') just=left asis=on protectspecialchars=off;
replace FooterEmphasis from Footer
/ font = fonts('EmphasisFootFont') just=left asis=on protectspecialchars=off;
replace FooterEmphasisFixed from FooterEmphasis
/ font = fonts('FixedEmphasisFootFont') just=left asis=on protectspecialchars=off;
replace FooterStrong from Footer
/ font = fonts('StrongFootFont') just=left asis=on protectspecialchars=off;
replace FooterStrongFixed from FooterStrong
/ font = fonts('FixedStrongFootFont') just=left asis=on protectspecialchars=off;
replace RowFooter from Footer
/ font = fonts('FootFont') asis=on protectspecialchars=off just=left;
replace RowFooterFixed from RowFooter
/ font = fonts('FixedFootFont') just=left asis=on protectspecialchars=off;
replace RowFooterEmpty from RowFooter
/ font = fonts('FootFont') just=left asis=on protectspecialchars=off;
replace RowFooterEmphasis from RowFooter
/ font = fonts('EmphasisFootFont') just=left asis=on protectspecialchars=off;
replace RowFooterEmphasisFixed from RowFooterEmphasis
/ font = fonts('FixedEmphasisFootFont') just=left asis=on protectspecialchars=off;
replace RowFooterStrong from RowFooter
/ font = fonts('StrongFootFont') just=left asis=on protectspecialchars=off;
replace RowFooterStrongFixed from RowFooterStrong
/ font = fonts('FixedStrongFootFont') just=left asis=on protectspecialchars=off;
replace SystemFooter from TitlesAndFooters / asis=on
protectspecialchars=off just=left;
end;
run;
quit;
%Mend utl_rtflan100;
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