Re: st: means compairison with weights and unequal variance

[Barbro Widerstedt <appoloniak@gmail.com>]

Sorry, I did not see your earlier answer  -- for some reason your
mails are archived as spam in gmail.

Thank you, I'll consider your answer. And try to de-spam you :)



On Tue, Nov 22, 2011 at 9:40 AM, Nick Cox <njcoxstata@gmail.com> wrote:
> 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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