BookmarkSubscribeRSS Feed
shami
Obsidian | Level 7

I would like to create  a table that looks like this:

DemographicsIdentified Missing Total
 N%N% 

PATIENT_COUNTY1

     

PATIENT_RACE1

     

PATIENT_ETHNICITY1

     

PATIENT_BIRTH_SEX1

     

PATIENT_DOB1

     


I have the following code below, I don't know how to proceed from here or if I'm doing the right thing or if this step is even necessary.

Thank you.

DATA WANT;
SET HAVE;

LENGTH PATIENT_COUNTY1 $20 
PATIENT_RACE1 $50
PATIENT_ETHNICITY1 $50
PATIENT_BIRTH_SEX1 $20 
PATIENT_DOB1 $50
GENDER_IDENTITY1 $20;

IF PATIENT_COUNTY = '' THEN PATIENT_COUNTY1 = 'MISSING';
ELSE PATIENT_COUNTY1 = 'IDENTIFIED';

IF PATIENT_RACE = '' THEN PATIENT_RACE1 = 'MISSING';
ELSE PATIENT_RACE1 = 'IDENTIFIED';

IF PATIENT_ETHNICITY = '' THEN PATIENT_ETHNICITY1 = 'MISSING';
ELSE PATIENT_ETHNICITY1 = 'IDENTIFIED';

IF PATIENT_BIRTH_SEX = '' THEN PATIENT_BIRTH_SEX1 = 'MISSING';
ELSE PATIENT_BIRTH_SEX1 = 'IDENTIFIED';

IF PATIENT_DOB = '' THEN PATIENT_DOB1 = 'MISSING';
ELSE PATIENT_DOB1 = 'IDENTIFIED';

IF GENDER_IDENTITY = '' THEN GENDER_IDENTITY1 = 'MISSING';
ELSE GENDER_IDENTITY1 = 'IDENTIFIED';

RUN;

 The above code gives me the following table:

ID

PATIENT_COUNTY1

PATIENT_RACE1

PATIENT_ETHNICITY1

PATIENT_BIRTH_SEX1

PATIENT_DOB1

1

IDENTIFIED

IDENTIFIED

MISSING

IDENTIFIED

MISSING

2

IDENTIFIED

IDENTIFIED

MISSING

IDENTIFIED

MISSING

3

IDENTIFIED

IDENTIFIED

MISSING

IDENTIFIED

MISSING

1 REPLY 1
Reeza
Super User

You can use SAS features, such as formats to make this easier. 

See this example (note this is overkill and generic code so possibly a little bit longer than what you need). You should just need to change the input data set name and desired output data set name to have it work for you.

/*This program creates a report with the number and percent of
missing data for each variable in the data set.
The ony change should be to the macro variable, INPUT_DSN.
Author: F. Khurshed
Date: 2019-01-04
*/
*create sample data to work with;

data class;
    set sashelp.class;

    if age=14 then
        call missing(height, weight, sex);

    if name='Alfred' then
        call missing(sex, age, height);
    label age="Fancy Age Label";
run;

*set input data set name;
%let INPUT_DSN = class;
%let OUTPUT_DSN = want;
*create format for missing;

proc format;
    value $ missfmt ' '="Missing" other="Not Missing";
    value nmissfmt .="Missing" other="Not Missing";
run;

*Proc freq to count missing/non missing;
ods select none;
*turns off the output so the results do not get too messy;
ods table onewayfreqs=temp;

proc freq data=&INPUT_DSN.;
    table _all_ / missing;
    format _numeric_ nmissfmt. _character_ $missfmt.;
run;

ods select all;
*Format output;

data long;
    length variable $32. variable_value $50.;
    set temp;
    Variable=scan(table, 2);
    Variable_Value=strip(trim(vvaluex(variable)));
    presentation=catt(frequency, " (", trim(put(percent/100, percent7.1)), ")");
    keep variable variable_value frequency percent cum: presentation;
    label variable='Variable' variable_value='Variable Value';
run;

proc sort data=long;
    by variable;
run;

*make it a wide data set for presentation, with values as N (Percent);

proc transpose data=long out=wide_presentation (drop=_name_);
    by variable;
    id variable_value;
    var presentation;
run;

*transpose only N;

proc transpose data=long out=wide_N prefix=N_;
    by variable;
    id variable_value;
    var frequency;
run;

*transpose only percents;

proc transpose data=long out=wide_PCT prefix=PCT_;
    by variable;
    id variable_value;
    var percent;
run;

*final output file;

data &Output_DSN.;
    merge wide_N wide_PCT wide_presentation;
    by variable;
    drop _name_;
    label N_Missing='# Missing' N_Not_Missing='# Not Missing' 
        PCT_Missing='% Missing' N_Not_Missing='% Not Missing' Missing='Missing' 
        Not_missing='Not Missing';
run;

title "Missing Report of &INPUT_DSN.";

proc print data=&output_dsn. noobs label;
run;

@shami wrote:

I would like to create  a table that looks like this:

Demographics Identified   Missing   Total
  N % N %  

PATIENT_COUNTY1

         

PATIENT_RACE1

         

PATIENT_ETHNICITY1

         

PATIENT_BIRTH_SEX1

         

PATIENT_DOB1

         


I have the following code below, I don't know how to proceed from here or if I'm doing the right thing or if this step is even necessary.

Thank you.

DATA WANT;
SET HAVE;

LENGTH PATIENT_COUNTY1 $20 
PATIENT_RACE1 $50
PATIENT_ETHNICITY1 $50
PATIENT_BIRTH_SEX1 $20 
PATIENT_DOB1 $50
GENDER_IDENTITY1 $20;

IF PATIENT_COUNTY = '' THEN PATIENT_COUNTY1 = 'MISSING';
ELSE PATIENT_COUNTY1 = 'IDENTIFIED';

IF PATIENT_RACE = '' THEN PATIENT_RACE1 = 'MISSING';
ELSE PATIENT_RACE1 = 'IDENTIFIED';

IF PATIENT_ETHNICITY = '' THEN PATIENT_ETHNICITY1 = 'MISSING';
ELSE PATIENT_ETHNICITY1 = 'IDENTIFIED';

IF PATIENT_BIRTH_SEX = '' THEN PATIENT_BIRTH_SEX1 = 'MISSING';
ELSE PATIENT_BIRTH_SEX1 = 'IDENTIFIED';

IF PATIENT_DOB = '' THEN PATIENT_DOB1 = 'MISSING';
ELSE PATIENT_DOB1 = 'IDENTIFIED';

IF GENDER_IDENTITY = '' THEN GENDER_IDENTITY1 = 'MISSING';
ELSE GENDER_IDENTITY1 = 'IDENTIFIED';

RUN;

 The above code gives me the following table:

ID

PATIENT_COUNTY1

PATIENT_RACE1

PATIENT_ETHNICITY1

PATIENT_BIRTH_SEX1

PATIENT_DOB1

1

IDENTIFIED

IDENTIFIED

MISSING

IDENTIFIED

MISSING

2

IDENTIFIED

IDENTIFIED

MISSING

IDENTIFIED

MISSING

3

IDENTIFIED

IDENTIFIED

MISSING

IDENTIFIED

MISSING


 

SAS Innovate 2025: Save the Date

 SAS Innovate 2025 is scheduled for May 6-9 in Orlando, FL. Sign up to be first to learn about the agenda and registration!

Save the date!

Mastering the WHERE Clause in PROC SQL

SAS' Charu Shankar shares her PROC SQL expertise by showing you how to master the WHERE clause using real winter weather data.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 345 views
  • 0 likes
  • 2 in conversation