UPDATE:
I solved the first part of the problem. I created unique ids for each observation:
gen id=_n
Then, I used
fillin id categ
which essentially created what I was looking for.
However, for the rest of the variables (except id and categ), almost all observations are missing. Now, I need your help to duplicate the rest of the variables instead of having them missing. Just as an example, each observation is associated with a particular week. I am missing most of them. Or another dummy variable indicates whether a purchase was made at a drug or grocery store. Most of them are missing too.
Thanks!
ORIGINAL MESSAGE:
Need your help in Stata!
Each observation in my database is a 1-unit purchase of a beer product made by a customer. These product purchases are categorized unto 8 general categories such that the variable "categ" has values from 1 to 8 (1=import, 2=craft, 3=premium, 4=light, etc). For my multinomial logit model, I need to observe all categories purchased or not purchased by the customer in each observation.
Assume, this is my initial dataset:
customer id-------beer category-----units purchased
----------1------------------1--------------------- 1
----------2----------------- 3--------------------- 1
----------3 -----------------2 ---------------------1
This is what I am looking for:
customer id-------beer category-----units purchased
----------1------------------1--------------------- 1
----------1 -----------------2 ---------------------0
----------1----------------- 3--------------------- 0
----------2----------------- 1--------------------- 0
----------2----------------- 3--------------------- 1
----------2 -----------------3--------------------- 0
----------3----------------- 1--------------------- 0
----------3----------------- 2--------------------- 0
----------3 -----------------2 ---------------------1
Currently, my dataset is 600,000 obs. After this procedure, I should have 600,000*8=4,800,000 obs.
When constructing this code, it is necessary that all other variables in the dataset are duplicated according to the associated category of beer.
I assume that "fillin" and less likely "expand" might work.
You help will tremendously help. Thanks!