I have been asked to calculate the Standardized difference for continuous and categorical variables. I understand how to do it for the continuous variables but am unsure how to do it for the binary categorical variables. This is the code I use for the continuous variables where x and y are the means of the two variables for the two groups Y =treated X = Untreated :
I use proc means to get the mean for the continuous variable in the untreated and treated groups first and then run the following code:
set Cohortfile;
| | if Var_Type='Cont' then do; |
length stddiff diff 8;
format stddiff 6.2 diff 8.4;
denomSD = sqrt((y_&varname_Treat**2 + x_&varname_UnTrt**2)/2);
diff = x_&varname_Treat - y_&varname_UnTrt;
if denomSD gt 0 then do;
stddiff = 100*(nx_&varname_Treat - ny_&varname_UnTrt)/denomSD;
end;
else stddiff = .;
end;
run;
For the Binary variables I am using proc freq to get total counts and percentages not proc means. Should I be using proc means. I am unsure how to get the SD without creating a mean value first.
My data set looks like this: For the continous variables Age and Medications I use proc means to produce a mean.
For the catagorical variables Diabetes Asthma etc I use proc freq to generate the count and percentage for my output table. So this is where I get stuck as with out a mean how do i produce the SD?
| Patient | Exposure | Age | Medications | Diabetes | Asthma | Smoking | Osteo | Fracture |
| 1 | 1 | 50 | 6 | 1 | 0 | 1 | 0 | 1 |
| 2 | 1 | 54 | 4 | 0 | 0 | 1 | 0 | 1 |
| 3 | 0 | 42 | 11 | 0 | 1 | 1 | 1 | 1 |
| 4 | 1 | 35 | 0 | 1 | 1 | 0 | 1 | 0 |
| 5 | 0 | 70 | 9 | 1 | 0 | 1 | 0 | 1 |
| 6 | 0 | 55 | 12 | 1 | 1 | 0 | 1 | 0 |
The table I am trying to create looks like this:
| | Before propensity score match |
| (N=xxx) |
| Baseline Characteristics | Treated | Untreated | Standardized Difference |
| (N=xx) | (N=xx) |
| Demographics | | | | |
| | Age – Mean | xx.x (xx.x) | xx.x (xx.x) | x.xxx |
| | Number of unique medications – Mean | xx.x (xx.x) | xx.x (xx.x) | x.xxx |
| Baseline Comorbidities | | | | |
| | Diabetes– count (%) | xx.x (xx.x) | xx.x (xx.x) | x.xxx |
| | Asthma – count (%) | xx.x (xx.x) | xx.x (xx.x) | x.xxx |
| | Smoking – count (%) | xx.x (xx.x) | xx.x (xx.x) | x.xxx |
| | Osteoporosis – count (%) | xx.x (xx.x) | xx.x (xx.x) | x.xxx |
| | Fracture – count (%) | xx.x (xx.x) | xx.x (xx.x) | x.xxx |
Many thanks in advance,
Lisa.
