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Barkat
Pyrite | Level 9

Below is a table from SAS result. What formula was used to calculate the "Std Err of Percent" in this table?

I know, SE of percent = (True percent - observed percent)/True percent. I believe the "Percent" column has the observed percent (correct me if I am wrong). I thought true percent for Male-Negative is 1*100/9=11.1%. So, SE of percent=(11.1-7.5605)/11,1=0.3189. But the table shows 7.5159. My brain is not working. Please help.

 

Gender Result Frequency Weighted
Frequency
Std Err of
Wgt Freq
Percent Std Err of
Percent
95% Confidence Limits
for Percent
Male Negative 1 16.20746 16.20746 7.5605 7.5259 0.0000 22.6253
  Positive 4 64.82982 31.56546 30.2419 14.4387 1.3398 59.1441
  Total 5 81.03728 34.96896 37.8024 15.9078 5.9594 69.6454
Fem Negative 3 100.00000 56.73086 46.6482 18.0779 10.4613 82.8350
  Positive 1 33.33333 33.33333 15.5494 14.1520 0.0000 43.8778
  Total 4 133.33333 64.91964 62.1976 15.9078 30.3546 94.0406
Total Negative 4 116.20746 58.52508 54.2087 17.5366 19.1054 89.3120
  Positive 5 98.16316 45.08850 45.7913 17.5366 10.6880 80.8946
  Total 9 214.37061 71.16743 100.0000      

 

 

3 REPLIES 3
ballardw
Super User

Show starting data in the form of a data step.

Show the code for creating that output.

 

Then we have some clue of what is going on.

Barkat
Pyrite | Level 9

Example of a starting data and SAS code are mentioned below. Actually, I am curious, what formula was used to calculate the "Std Err of Percent" in the back end?

 

data have;                      
   input ID Gender $ Result $;     
   datalines; 
1 Male  Positive
2 Male Negative
3 Female Negative
4 Female  Negative
5 Male  Positive
6 Male Positive
7 Female Positive
8 Female  Negative
9 Male  Positive
;  

Data have; set have;
if Gender="Male" then Prob=0.0617;
if Gender="Female" then Prob=0.0300;
Wt=1/Prob;
run;

proc surveyfreq data=have;
table Gender*Result  /  cl; 
Weight wt;
run;
SAS_Rob
SAS Employee

This appears to be output from Proc SURVEYFREQ which means the standard errors are calculated factoring in the design effect (strata, cluster and weight).  There are a number of different methods (controlled by the VARMETHOD= option on the SURVEYFREQ statement) for calculating them so I would suggest you reference the documentation:

SAS Help Center: Proportions

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