You can also use your own distance measure by
distance = pscore
where pscore is a vector of your own distance measure.
Kosuke
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Kosuke Imai Office: Corwin Hall 041
Assistant Professor Phone: 609-258-6601
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On Dec 19, 2005, at 2:00 PM, Gary King wrote:
On Fri, 16 Dec 2005, Jeanie (Jie) Na wrote:
Hi Dr. King,
I am learning to use MatchIt package in R for a project I am
working on.
I have a couple of questions when I read about the manual.
1) I have a few categorical variables with multiple levels and a few
continuous variables as covariates. The examples given in the
manual of
MatchIt seem to have all the covariates as dichotomous or
continuous. Do
I need to recode my data and give them values 1 to n (# of levels)?
It doesnt seem to be ok as of now when I have character values for
those
categorical variables.
you can exact match on fully category variables. otherwise, i
think you'd want to make them into 'continuous' variables as you
would right side variables in a regression (such as a set of J-1
dummies coding J categories for a nominal variable)
2) can you give me an example of the command if I want to use my own
distance measure? What would be the input for distance? Will it be a
distance matrix with rows for the treated,columns for the controlled,
and values are the abs(logit(propensity score of control
i)-logit(propensity score of treated j)). Or would it be a matrix
with
propensity scores as one column?
the program allows you to estimate the distance based on
Mahalanobis distance or the propensity score computed in a variety
of ways. if you need different metrics you might need to explain
some more about what you're looking for.
Best of luck,
Gary King
I hope I explained myself well. Thank you very much for your advice.
--
Jeanie (Jie) Na
Programmer Analyst II _ _ ___
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Department of Quantitative Health Sciences [_]-[_] / - \ | |
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Cleveland Clinic Foundation | | ( |_| ) )
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Tel: (216)4451369 [_]-[_] \_\_\ |
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