[R] propensity score adjustment using R
ben.domingue at gmail.com
Thu Sep 18 19:32:21 CEST 2008
I'm not quite sure what you mean. If all you need is propensity
scores to run an IPW analysis, the fitted values should work. Having
many binary covariates shouldn't be a problem, the whole point of the
propensity score is boiling down many dimensions to a single one.
I use matchit() for my psm needs, but it may not be so useful for IPW.
On Thu, Sep 18, 2008 at 11:00 AM, ran2 <bunny at lautloscrew.com> wrote:
> Frank E Harrell Jr wrote:
>> That is a high variance procedure as compared with covariate adjustment
>> using the propensity score, or stratification.
>> Frank Harrell
> Ah, wait what if I got very high dimensional X ? Even with 20 binary
> covariates i would end up with more than 1 million possibilities...
> View this message in context: http://www.nabble.com/propensity-score-adjustment-using-R-tp19555722p19557409.html
> Sent from the R help mailing list archive at Nabble.com.
> R-help at r-project.org mailing list
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
More information about the R-help