Multiple categories of the treatvar


This post shows various examples of using template(table1) when the treatment variable has more than two categories. If you are new to asdocx or to the template(table1), you may like to start with the basic introduction to Table1 template here.

Several asdocx users requested to add support for multiple categories of the treatment variable. In asdocx version 2.1.2 (Aug 17, 2022) this is now possible. Following are few examples:

Example data


use http://fintechprofessor.com/asdocxAddins/table1svy, clear

* Create a dummy variable to use it a continuous variable
gen pincome = id / 10000

* Create value lable for gener
label define genderlable 1 "Female" 0 "Male"

* assign values
label value gender genderlable

Continuous variables


   *1. mean ci - for comparison, firstoutput from Stata 
		
   	mean pincome, over(mi_final)  

Mean estimation                         Number of obs   =     18,076

--------------------------------------------------------------------
                   |       Mean   Std. Err.     [95% Conf. Interval]
-------------------+------------------------------------------------
c.pincome@mi_final |
             none  |   4.937284   .0184639      4.901093    4.973475
            stemi  |    4.65329   .4590964      3.753418    5.553163
           nstemi  |   5.241515   .2427136      4.765773    5.717256
           Type 2  |   4.401919   .4269773      3.565002    5.238835
--------------------------------------------------------------------

	asdocx tab mi_final pincome , template(table1) replace landscape  cont(mean ci)
Table 1: Demographics
Variables none (n=17932) stemi (n=21) nstemi (n=96) Type 2 (n=27) Total (18076) P-value
pincome 4.937 (4.901 – 4.973) 4.653 (3.753 – 5.553) 5.242 (4.766 – 5.717) 4.402 (3.565 – 5.239) 4.938 (4.902 – 4.974) 0.887
P-values by t-test for continuous variables and Chi2 test for binary/categorical variables.
   *2. svy mean ci 	

svyset id [pweight=dwt], vce(linearized) 
svy: mean income, over(mi_final)
--------------------------------------------------------------------
                   |             Linearized
                   |       Mean   Std. Err.     [95% Conf. Interval]
-------------------+------------------------------------------------
c.pincome@mi_final |
             none  |   4.937284    .056669      4.826177     5.04839
            stemi  |   4.653291   .4480933       3.77475    5.531833
           nstemi  |   5.241515    .248015      4.755251    5.727779
           Type 2  |    4.40192   .4190554      3.580311     5.22353
--------------------------------------------------------------------

    svy: mean pincome, over(mi_final)  
    asdocx svy: tab mi_final pincome, template(table1) replace ///
    landscape cont(mean ci)
Table 1: Demographics
Variables none (n=17932) stemi (n=21) nstemi (n=96) Type 2 (n=27) Total (18076) P-value
pincome 4.937 (4.826 – 5.048) 4.653 (3.775 – 5.532) 5.242 (4.755 – 5.728) 4.402 (3.580 – 5.224) 4.938 (4.827 – 5.049) 0.887
P-values by t-test for continuous variables and Chi2 test for binary/categorical variables.
    *3. mean sd 		
    mean pincome, over(mi_final)  
	estat sd
	asdocx tab mi_final pincome, template(table1) replace ///
        landscape cont(mean sd)

   *4. svy mean sd 	
    svy:mean pincome, over(mi_final)  
	estat sd
	asdocx svy:tab mi_final pincome , template(table1) /// 
        landscape  cont(mean sd)
*------------------------------------------------------------------------------
**# 		Factor variables (gender is a factor variable)
*=============================================================================*/


   *1. count and cell percentage
   	tab gender mi_final, cell
	asdocx  tab mi_final pincome gender, template(table1) /// 
        replace landscape cont(mean sd) cell

   *2. count and row percentage	
   	tab gender mi_final, row
	asdocx tab mi_final pincome gender, template(table1) /// 
        replace landscape cont(mean sd) row

   *3. count and column percent	
   	tab gender mi_final, col
	asdocx  tab mi_final pincome gender, template(table1) /// 
        replace landscape cont(mean sd) col

   
   *4. svy count and cell
   	svy:tab gender mi_final, cell format(%9.5f)
	asdocx svy:tab mi_final pincome gender, template(table1) ///
        replace landscape cont(mean sd) cell

   *5. svy count and row 
   	svy:tab gender mi_final,  format(%9.5f) row
	asdocx  svy:tab mi_final pincome gender, template(table1) ///
        replace landscape cont(mean sd) row

   * 6. svy count and column
   	svy:tab gender mi_final,  format(%9.5f) col
	asdocx  svy:tab mi_final pincome gender, template(table1) ///
        replace landscape cont(mean sd) col