Suppose I have the following table:
id | car | sex | income
-------------------------------
1 | European | Male | 45000
2 | Japanese | Female | 48000
3 | American | Male | 53000
I would like to create the one below:
| id | car | choice | sex | income
--------------------------------------------
1.| 1 | European | 1 | Male | 45000
2.| 1 | American | 0 | Male | 45000
3.| 1 | Japanese | 0 | Male | 45000
| ----------------------------------------
4.| 2 | European | 0 | Female | 48000
5.| 2 | American | 0 | Female | 48000
6.| 2 | Japanese | 1 | Female | 48000
| ----------------------------------------
7.| 3 | European | 0 | Male | 53000
8.| 3 | American | 1 | Male | 53000
9.| 3 | Japanese | 0 | Male | 53000
I would like to fit an asclogit
and according to Example 1 in Stata's Manual, this table format seems necessary. However, i have not found a way to create this easily.
You can use the cross
command to generate all the possible combinations:
clear
input byte id str10 car str8 sex long income
1 "European" "Male" 45000
2 "Japanese" "Female" 48000
3 "American" "Male" 53000
end
generate choice = 0
save old, replace
keep id
save new, replace
use old
rename id =_0
cross using new
replace choice = 1 if id_0 == id
replace sex = cond(id == 2, "Female", "Male")
replace income = cond(id == 1, 45000, cond(id == 2, 48000, 53000))
Note that the use of the cond()
function here is equivalent to:
replace sex = "Male" if id == 1
replace sex = "Female" if id == 2
replace sex = "Male" if id == 3
replace income = 45000 if id == 1
replace income = 48000 if id == 2
replace income = 53000 if id == 3
The above code snipped produces the desired output:
drop id_0
order id car choice sex income
sort id car
list, sepby(id)
+------------------------------------------+
| id car choice sex income |
|------------------------------------------|
1. | 1 American 0 Male 45000 |
2. | 1 European 1 Male 45000 |
3. | 1 Japanese 0 Male 45000 |
|------------------------------------------|
4. | 2 American 0 Female 48000 |
5. | 2 European 0 Female 48000 |
6. | 2 Japanese 1 Female 48000 |
|------------------------------------------|
7. | 3 American 1 Male 53000 |
8. | 3 European 0 Male 53000 |
9. | 3 Japanese 0 Male 53000 |
+------------------------------------------+
For more information, type help cross
and help cond()
from Stata's command prompt.