Re: st: means compairison with weights and unequal variance

[Nick Cox <njcoxstata@gmail.com>]

See also the suggestions made earlier in the thread at

http://stata.com/statalist/archive/2011-11/msg01010.html

Nick

On Tue, Nov 22, 2011 at 8:16 AM, Barbro Widerstedt <appoloniak@gmail.com> wrote:
> 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

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