in proc means one can use CLM to get the confidence interval of the mean. How to output the CLM to a dataset?
proc means data=adxe N NMISS CLM ;
by trtp;
var aval;
where aval >.;
/* output out=TFMT2RD n=n mean=mean std=sd median=median min=min max=max q1=q1 q3=q3 ;*/
run;
in proc univariate, what is the option to do thid? cibasic (alpha=0.05)?
what are the output options to get the 95% CI of mean?
proc univariate data=adxe cibasic (alpha=0.05) noprint;
by trtp;
var aval;
where aval >.;
output out=TFMT2RD n=n mean=mean std=sd median=median min=min max=max q1=q1 q3=q3 ;
run;
Note: You can also output them directly, but the above method is a lot more versatile. Additionally, if you use any of the special missing values (e.g., .A, .B, etc), you can capture all of them by using where not missing(variablename). e.g.:
data class; set sashelp.class; if _n_ in (2,4,6) then weight=.; else if _n_ in (3,5,7) then weight=.A; run; proc means data=class N NMISS CLM nway ; class sex; var weight; where weight >.; output out=want /autoname; run; proc summary data=class N NMISS CLM nway; class sex; var weight; where weight >.; output out=want2 /autoname; run; proc means data=class N NMISS CLM nway ; class sex; var weight; where not missing(weight); output out=want3 /autoname; run; proc summary data=class N NMISS CLM nway; class sex; var weight; where not missing(weight); output out=want4 /autoname; run;
Art, CEO, AnalystFinder.com
You can use the following method with any procedure:
ods trace on; proc means data=sashelp.class N NMISS CLM; class sex; var weight; where weight >.; /* output out=TFMT2RD n=n mean=mean std=sd median=median min=min max=max q1=q1 q3=q3 ;*/ run; ods trace off; /*get the name of the desired file from the log*/ ods output Means.Summary=want; proc means data=sashelp.class N NMISS CLM; class sex; var weight; where weight >.; /* output out=TFMT2RD n=n mean=mean std=sd median=median min=min max=max q1=q1 q3=q3 ;*/ run;
Art, CEO, AnalystFinder.com
Note: You can also output them directly, but the above method is a lot more versatile. Additionally, if you use any of the special missing values (e.g., .A, .B, etc), you can capture all of them by using where not missing(variablename). e.g.:
data class; set sashelp.class; if _n_ in (2,4,6) then weight=.; else if _n_ in (3,5,7) then weight=.A; run; proc means data=class N NMISS CLM nway ; class sex; var weight; where weight >.; output out=want /autoname; run; proc summary data=class N NMISS CLM nway; class sex; var weight; where weight >.; output out=want2 /autoname; run; proc means data=class N NMISS CLM nway ; class sex; var weight; where not missing(weight); output out=want3 /autoname; run; proc summary data=class N NMISS CLM nway; class sex; var weight; where not missing(weight); output out=want4 /autoname; run;
Art, CEO, AnalystFinder.com
I am a little confused don't you get the intervals
title 'Analysis of Female Heights';
ods select BasicIntervals;
proc univariate data=sashelp.class cibasic;
var Height;
run;
The UNIVARIATE Procedure
Variable: HEIGHT
Basic Confidence Limits Assuming Normality
Parameter Estimate 95% Confidence Limits
Mean 62.33684 59.86567 64.80801
Std Deviation 5.12708 3.87408 7.58204
Variance 26.28690 15.00852 57.48740
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