Hello,
I am working with data that includes a subset of variables for each member of a HH. I have a series of variables that index information in the following manner
intern_12m_[i=1-55] --> a variable for whether someone migrated, i indexes the household member number.
intern_months_[i=1-34]_[j=1-12] --> a variable that lists the months in which the episode occurred, i indexes the member number, j indexes the migration episode number of the member (max 12 b/c one episode defined as absence for at least 1 month).
---ex. intern_months_3_4 lists the months of member 3's 4th migration episode.
But- unfortunately- the data also contain dummies for each member x episode x month combination, and I'd like to drop these because I get this information from the variable above. The variables are of the following format:
intern_months_[j=1-12]_[i=1-34]_[k=1-12] --> a dummy if a migration episode for a member occurred in month k.
I've transformed data from long to wide with
and the data is in the current format (I ommitted the remaining intern_months_ variables bc dataex limits exceeded)
------------------ copy up to and including the previous line ------------------
Now I want to reshape the intern_months_[i=1-34]_[j=1-12] variables to long format as well by first dropping the intern_months_[j=1-12]_[i=1-34]_[k=1-12] dummy variables. I don't know to reference these bc the variables are not constant across these indices. For example, the maximum number of episodes for a "1st" member household is 7, and 6 for the 2nd member so doing something like:
results in messages that certain variables aren't found. Is there another way to think about how to approach this transformation process?
Thank you.
I am working with data that includes a subset of variables for each member of a HH. I have a series of variables that index information in the following manner
intern_12m_[i=1-55] --> a variable for whether someone migrated, i indexes the household member number.
intern_months_[i=1-34]_[j=1-12] --> a variable that lists the months in which the episode occurred, i indexes the member number, j indexes the migration episode number of the member (max 12 b/c one episode defined as absence for at least 1 month).
---ex. intern_months_3_4 lists the months of member 3's 4th migration episode.
But- unfortunately- the data also contain dummies for each member x episode x month combination, and I'd like to drop these because I get this information from the variable above. The variables are of the following format:
intern_months_[j=1-12]_[i=1-34]_[k=1-12] --> a dummy if a migration episode for a member occurred in month k.
I've transformed data from long to wide with
Code:
reshape long name_first_ name_last_ intern_12m_ , i(hhid) j(member)
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input str9 hhid byte(member intern_12m_) str26 intern_months_1_1 "1--66-1" 1 0 "" "1--66-1" 2 0 "" "1--66-1" 3 0 "" "1-1-1" 1 0 "" "1-1-1" 2 0 "" "1-1-1" 3 1 "" "1-1-1" 4 0 "" "1-1-2" 1 0 "" "1-1-2" 2 0 "" "1-1-2" 3 0 "" "1-1-2" 4 0 "" "1-1-2" 5 0 "" "1-1-2" 6 0 "" "1-1-3" 1 0 "" "1-1-3" 2 0 "" "1-1-3" 3 0 "" "1-1-3" 4 0 "" "1-1-3" 5 1 "" "1-1-3" 6 0 "" "1-1-3" 7 0 "" end
Now I want to reshape the intern_months_[i=1-34]_[j=1-12] variables to long format as well by first dropping the intern_months_[j=1-12]_[i=1-34]_[k=1-12] dummy variables. I don't know to reference these bc the variables are not constant across these indices. For example, the maximum number of episodes for a "1st" member household is 7, and 6 for the 2nd member so doing something like:
Code:
forvalues x=1/12 {
forvalues y=1/34 {
forvalues z=1/12 {
drop intern_months_`x'_`y'_`z'
}
}
}
Thank you.
