Hi all!
First time here
I'm looking for a neat way to arrange frequency statistics (percentage of positive response) for a large set (~55) of binary variables in a data set.
I am familiar with PROC FREQ, but it makes 55 distinct tables, and this is inelegant when presenting the work to others.
Is there a more elegant way to do what I need? (i.e. arrange those 55 percentages?)
Thanks very much!,
Assuming 0/1 coding and not some other binary.
proc tabulate data=your dataset name;
var var1-var50;
table var1-var50,n='Count' sum='Number of ones' mean= 'Percent ones'*f=percent10.2;
run;
Assuming you have an ID variable identifying each observation, as in the following example :
/* Example dataset */
data test;
array x{15};
do id = 1 to 10;
do i = 1 to dim(x);
x{i} = rannor(-1);
end;
output;
end;
run;
proc transpose data=test out=list;
var x:; /* x: is the list of variable names */
by id;
run;
/* calculate the percentages with SQL */
proc sql;
select _name_ as variable label="Variable", sum(col1>0)/count(*) as pctPos format=percent7.1 label="Percent positive"
from list
group by _name_;
quit;
PG
The MEAN of 0/1=Proportion, N=N, and SUM=COUNT.
PROC CORR?
data test;
array x[15];
do id = 1 to 10;
trt = rantbl(123,.55);
do i = 1 to dim(x);
x = rantbl(123,.3)-1;
end;
output;
end;
run;
proc sort data=test;
by trt;
run;
ods output
SimpleStats=stats
(
keep=trt var: nobs mean sum
rename=(mean=pct sum=count)
)
;
proc corr nocorr;
by trt;
var x:;
run;
proc print;
format pct percent8.1;
run;
If you have 55 variables with 1/0 then I'd use proc means to get the stats suggested by data _null_ and create a table that you could sort descending and/or use to create a bar chart as well.
Assuming 0/1 coding and not some other binary.
proc tabulate data=your dataset name;
var var1-var50;
table var1-var50,n='Count' sum='Number of ones' mean= 'Percent ones'*f=percent10.2;
run;
Thank you all very much! I learned a lot!
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