Re: st: Conditional matching of observations

[sjsamuels@gmail.com]

The technical answer to your question is simple: give every person in
A (receive support) a pseudo-age and and gender which you will use to
match to people in B (do not receive support). Then use one of Stata's
many matching programs to match on race, pseudo-age, and
pseudo-gender.

Female in A: pseudo-age = age +3 pseudo-gender = male
Male in A:  pseudo-age = age-3 pseudo-gender = female

Female in B:  pseudo-age = age pseudo-gender =female
Male in B:  pseudo-age = age pseudo-gender = male


However I question your basic design. Even if the average age of males
paying child support to females is three years older than the females
they support, it is not exactly three years older in every case. Your
matched population of potential payers  will match the actual
population only in mean difference in age but not in any other
characteristics, such as the quantiles of the difference. Also the
population B who do not receive child support will include a
supopulation, B', approximately equal in size to A, who already pay
child support to someone in A.   You are also ignoring geographical
proximity, which is important for many phenomena. Will ignoring these
issues cause problems? Without knowing the purpose and details of your
study it is difficult to say much more.

Steve
On Wed, Mar 3, 2010 at 6:08 PM, Nathan Hutto <nathandavidhutto@gmail.com> wrote:
>
> I have a large population data set. I want to match people who have
> received child support payments (0/1) to a person who could have
> theoretically paid them child support. I want to match on sex, race,
> and age only. For each person who receives child support, I want to
> match to someone of the opposite sex and same race. If the person
> receiving is a female, her match should be 3 years older. If the
> person receiving the match is a male, his match should be 3 years
> younger. I have no idea how to go about do this after searching high
> and low for an appropriate method. Any help would be much appreciated.
>
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