> > Speaking of standard errors, when correcting for heteroscedasticity,
> > how many matches do you use (this is the Var.cal option).  It seems to
> > me that it might make sense to use the same number of matches as
> > above, but that's just a guess...
>
> These are related but separate issues.  The number of matches is all
> about covariate balance (bias reduction).  And the Var.cal option is
> related to the heterogeneity of the causal effect.  It could be that
> the data is such that one needs to do 1-to-1 matching to get good
> covariate balance, but that the causal effect is homogeneous so
> Var.cal can be set to 0 etc.

Ok, but in my case, I think that the treatment effect *is*
hetergenous, and I even partition my sample based on a number of
characteristics and find very different effects for these subsamples. 
Given that, it seems that I certainly should not use Var.cal=0.

My question is how do I go about deciding what I should set Var.cal
equal to?  Should it be 1, or perhaps the number of matches I use for
the treatment effect?

Regards,

Brian

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