How do I "conditionally" count missing values per variable in PROC SQL? - sql

Question

I'm measuring expenses in different categories. I have two types of variables. A categorical variables which states if the respondent have had expenses in the category (such as "Exkl_UtgUtl_Flyg") and I have numerical variables (such as UtgUtl_FlygSSEK_Pers), which provides information on the amount spent by each respondent in that category.
I want to create a table which tells me if there are missing values in my numerical variables for categories where expenses have been reported (so missing values of "UtgUtl_FlygSSEK_Pers" where the variable "Exkl_UtgUtl_Flyg" equals 1, in an example with only one variable).
This works in a simple SQL query, so something like:
PROC SQL;
SELECT nmiss(UtgUtl_FlygSSEK_Pers)
FROM IBIS3_5
WHERE Exkl_UtgUtl_Flyg=1;
quit;
But I don't want to navigate between 20 different datasets to find my missing values, I want them all in the same table. I figure this should be possible if i write a subquery in the SELECT clause for each variable, so something like:
PROC SQL;
SELECT (SELECT nmiss(UtgUtl_FlygSSEK_Pers)
FROM IBIS3_5
WHERE Exkl_UtgUtl_Flyg=1) as nmiss_variable_1
FROM IBIS3_5;
quit;
This last query does not seem to work, however. It does not return a single value, but one value for each row in the dataset.
How do I make this work?

Answer 1

I suspect you want to generate a single value.
Either the total number of mis-matches.
select sum(missing(UtgUtl_FlygSSEK_Pers) and Exkl_UtgUtl_Flyg=1) as nmiss
from ibis3_5
;
Or perhaps just a binary 1/0 flag of whether or not there are any mismatches.
select max(missing(UtgUtl_FlygSSEK_Pers) and Exkl_UtgUtl_Flyg=1) as any_miss
from ibis3_5
;

Answer 2

Maybe a good usage of proc freq instead. Especially if you have multiple values.
Not all of this is necessary but this is a missing report. Depends exactly how you're defining missing of course.
*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;