Re: st: means compairison with weights and unequal variance

[Barbro Widerstedt <appoloniak@gmail.com>]

Now I feel a bit stupid -- of course. It is what I do for other
outcomes, and the strategy should be as valid in this case... I'll
have a look and see if they give me the same conclusion at p<0.05



On Mon, Nov 21, 2011 at 7:45 PM, Ariel Linden, DrPH
<ariel.linden@gmail.com> wrote:
> Why not simply use -regress- and the weight generated in -cem- (cem_weights)
> as the aweight with robust se? This is the approach suggested by the
> authors. See:
>
> Stefano M. Iacus, Gary King, and Giuseppe Porro, "Matching for Causal
> Inference Without Balance Checking", copy at
> <http://gking.harvard.edu/files/abs/cem-abs.shtml>
>
> Ariel
>
>
>
> Date: Sun, 20 Nov 2011 21:40:40 -0800
> From: John Luke Gallup <jlgallup@pdx.edu>
> Subject: Re: st: means compairison with weights and unequal variance
>
> Barbro,
>
> A simple alternative is to calculate the means and standard deviations for
> each group using -summarize- with weights, and then run -ttesti ...,
> unequal-:
>
> sysuse auto, clear
>
> sum mpg if foreign [aw=weight]
> local N1 = r(N)
> local av1 = r(mean)
> local sd1 = r(sd)
>
> sum mpg if !foreign [aw=weight]
> local N2 = r(N)
> local av2 = r(mean)
> local sd2 = r(sd)
>
> ttesti `N1' `av1' `sd1' `N2' `av2' `sd2', unequal
>
> John
>
> John Luke Gallup
> Department of Economics
> Portland State University
>
> On Nov 20, 2011, at 2:13 AM, appoloniak wrote:
>
>> Hello statslisters,
>>
>> [caveat: sorry if this is a FAQ, but sometimes my imagination in
>> creating queries for use in the archives gives me nothing... and it is
>> more of a statistics that a Stata question, so please don't hit me too
>> hard ... ]
>>
>> I have a dataset where I try to compare the means of a variable
>> between two groups (treated and untreated).
>> The data set used is a sample, drawn from the superpopulation by the
>> ado-package cem (Iaucus et al Coarsened enhanced mathing), and
>> subsequent estimations should be weighted.
>>
>> This means that a standard t-test cannot be used, and I searched a bit
>> and found that <oneway> is an alternative with weighted data. However,
>> the groups have unequal variance which is a problem for <oneway> (at
>> least I think so, I know ANOVA mainly by name ...). I read one entry
>> that suggests that oneway is robust to  groupwise unequal  variance if
>> groupsize does not vary too much, but in my case they do (min
>> groupsize=2 max groupsize=1273)
>>
>> ttest <outcome>, by(treatvar) unequal -> t = -2.43
>> oneway <outcome> <treatvar> [aweight=cem_weight] -> F=4.06
>>
>> both bartlett's test for equality of variance,  a standard sdtest ,
>> and robvar suggest that I have unequal variance between groups.
>>
>> Suggestion on alternatives would be greatly appreciated
>>
>> /Barbro Widerstedt
>
>
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