Reply To: How to report row percentage and confidence interval using table1 template

[Attaullah Shah]

#17600

I have added the requested feature. First update asdocx with

asdocx_update

. Here is an example.

* Create a toy example
*generate random number of observations
clear 
set obs 200

* create variable for using sleeping pills
gen use_pills = round(runiform(0,1))
label define use_pills 0 "Yes" 1 "No"
label val use_pills use_pills
label var use_pills "Used sleeping pills in the last month"

 *create variable for male and female
gen gender = round(runiform(0,1))
label define gender 0 "Female" 1 "Male"
label val gender gender
replace use_pills = 1 if gender == 1 & use_pills == 0 & runiform()<0.7
replace use_pills = 0 if gender == 0 & use_pills == 1 & runiform()<0.3

Row percentage with confidence intervals

---

* if row percentages are required

asdocx tab use_pills gender, template(table1) row cat(% ci) replace 

Table 1: Demographics

Variables	Yes (n=79)	No (n=121)	Total (200)	P-value
gender				0.000
Female	64.444% (53.921 - 73.735)	35.556% (26.265 - 46.079)	100.000%
Male	19.091% (12.731 - 27.622)	80.909% (72.378 - 87.269)	100.000%
P-values by t-test for continuous variables and Chi2 test for binary/categorical variables.

* If the total column is not required, use option nototal
* Add option table_layout(auto) for auto adjust columns for contents
asdocx tab use_pills gender, template(table1) row cat(% ci) /// 
replace nototal table_layout(auto)

Table 1: Demographics

Variables	Yes (n=79)	No (n=121)	P-value
gender			0.000
Female	64.444% (53.921 - 73.735)	35.556% (26.265 - 46.079)
Male	19.091% (12.731 - 27.622)	80.909% (72.378 - 87.269)
P-values by t-test for continuous variables and Chi2 test for binary/categorical variables.

Column percentages

* If col percentages 
asdocx tab use_pills gender, template(table1) col categorical(% ci) replace 

Table 1: Demographics

Variables	Yes (n=79)	No (n=121)	Total (200)	P-value
gender				0.000
Female	73.418% (62.455 - 82.097)	26.446% (19.294 - 35.097)	45.0% (38.203 - 51.989)
Male	26.582% (17.903 - 37.545)	73.554% (64.903 - 80.706)	55.0% (48.011 - 61.797)
P-values by t-test for continuous variables and Chi2 test for binary/categorical variables.