## 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

```