Hi,
If I understand well, if I use different distance measures with the distance argument in
matchit(), then the genetic method will used those distance measures to do mathching
within matchit() ? Am I right ? I tried that approach, but I can't be sure that the
genetic method effectively use the distance argument from matchit(), since that method is
a stochastic algorithm which doesn't give the same answers anyway with tha same
distance measure.
As an aside, I read the documentation for Jas Sekhon’s GenMatch function and I used
GenMatch() direcly , but there is no object produces by GenMatch() which gives a distance
value for each observation. There is only a "Weight.matrix" object which gives a
weight for each variable and a "matches" object which gives a weigh for each
matches pair.
Thanks,
François Maurice, B. Sc., A. Stat.
Candidat à la maîtrise
Département de sociologie
Université de Montréal
De : "Stuart, Elizabeth A." <estuart(a)jhsph.edu>
À : Francois Maurice <maurice.francois(a)ymail.com>
Envoyé le : Lundi 15 Août 2011 9h14
Objet : Re: [matchit] Distance values from Genetic matching
Hi,
Genetic matching uses the same propensity score as the other methods (at least partially);
the difference is that it uses a different algorithm (and some other information on the
covariates) to actually pick the matches.
The genetic matching algorithm MatchIt uses is from Jas Sekhon’s GenMatch function. You
can read more about it here, which explains the distance measure used and the algorithm:
http://sekhon.berkeley.edu/matching/
Here is a brief description from that website: “GenMatch finds optimal balance using
multivariate matching where a genetic search algorithm determines the weight each
covariate is given. The user can choose which function of covariate balance to optimize
from a list or provide one of her own.”
So the “distance” in genetic matching is still just the propensity score, but because the
algorithm is different from nearest neighbor matching you get different matches.
Liz
On 8/14/11 11:37 AM, "Francois Maurice" <maurice.francois(a)ymail.com>
wrote:
Hi,
I'm trying to implement the ideas in Harder, Stuart and Anthony (2010), to seperate
the estimation step from the application step and that way to combine various mathcing
methods with various distance measures.
But I have a problem with genetic mathing. Is there a way to obtain distance values from
genetic mathcing (method="genetic") ? The distance values for the genetic method
obtain from the matchit() object are the same as those when choosing
method="nearest" and distance="logit" (the final results are not the
same).
Thanks,
François Maurice, B. Sc., A. Stat.
Candidat à la maîtrise
Département de sociologie
Université de Montréal