Hi,
I wonder if there is any easy way to modify my code below to generate 95% CI associated with the column percentage in each cell.
proc tabulate data=test2 missing noseps;
class score_cat Age65_lst1yr cat_avg_ip ;
class cat_race_re Cat_raceeth ;
table score_cat,(all Age65_lst1yr*cat_avg_ip*cat_race_re Age65_lst1yr*cat_avg_ip*Cat_raceeth)*(n*f=comma8. colPctN*f=4.1);
run;
All variables above are categorical ones with multiple levels. Any suggestion would be greatly appreciated!
Not in Tabulate for any of PCTN, COLPCTN, ROWPCTN or PAGEPCTN statistics. The statistics LCLM and UCLM for confidence limits may only be applied to VAR variables, or in other words, numeric variables that appear on a VAR statement.
So you need different data.
Or a different procedure that will produce confidence limits of proportions such as SURVEYFREQ to create the data of the summary desired and then display that data with a report procedure.
@Crystal_F wrote:
Hi,
I wonder if there is any easy way to modify my code below to generate 95% CI associated with the column percentage in each cell.
proc tabulate data=test2 missing noseps; class score_cat Age65_lst1yr cat_avg_ip ; class cat_race_re Cat_raceeth ; table score_cat,(all Age65_lst1yr*cat_avg_ip*cat_race_re Age65_lst1yr*cat_avg_ip*Cat_raceeth)*(n*f=comma8. colPctN*f=4.1); run;
All variables above are categorical ones with multiple levels. Any suggestion would be greatly appreciated!
Not in Tabulate for any of PCTN, COLPCTN, ROWPCTN or PAGEPCTN statistics. The statistics LCLM and UCLM for confidence limits may only be applied to VAR variables, or in other words, numeric variables that appear on a VAR statement.
So you need different data.
Or a different procedure that will produce confidence limits of proportions such as SURVEYFREQ to create the data of the summary desired and then display that data with a report procedure.
@Crystal_F wrote:
Hi,
I wonder if there is any easy way to modify my code below to generate 95% CI associated with the column percentage in each cell.
proc tabulate data=test2 missing noseps; class score_cat Age65_lst1yr cat_avg_ip ; class cat_race_re Cat_raceeth ; table score_cat,(all Age65_lst1yr*cat_avg_ip*cat_race_re Age65_lst1yr*cat_avg_ip*Cat_raceeth)*(n*f=comma8. colPctN*f=4.1); run;
All variables above are categorical ones with multiple levels. Any suggestion would be greatly appreciated!
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