Steven, thanks a lot for the advice regarding sampsi, and for additional comments. I'll definitely look into it.
Best wishes,
Alex
-----Opprinnelig melding-----
Fra: [email protected] [mailto:[email protected]] P� vegne av Steven Samuels
Sendt: 13. mai 2008 05:13
Til: [email protected]
Emne: Re: SV: st: Control groups
Alexander, you can use -sampsi- as a rough guide for stratified sampling, provided that the relative sampling fractions (treatment/
control) do not differ much between strata.
I don't know this area, but do you really want to do a hypothesis test? It sounds like you want to estimate proportions of people who respond to a campaign over time or at all. The control group provides the proportion who freely respond in the absence of a campaign. A test of zero campaign effect does not seem relevant. Wouldn't the more pertinent questions be: how big an effect, answered with confidence intervals; or a null hypothesis that the effect is at most some quantity "D", with alternative effect>D. The CI approach (but not a hypothesis test) can incorporate finite-population corrections. See any sampling book for details.
-Steven
On May 12, 2008, at 4:10 PM, <[email protected]>
<[email protected]> wrote:
> Carlo, thanks for pointing me to sampsi!
>
> Steven, sorry about being sparse with information. I actually had many
> different study designs in mind. Sometimes I will be using simple
> random sampling, and don't intend to generalize my findings.
> Then all I am planning to do is testing whether proportions in treated
> versus control are different. Also, my control group is internal.
>
> However, from time to time I would like to draw a stratified sample,
> otherwise using the same approach as above. The way I understand you
> sampsi would not be appropriate?
>
> Also, one particular study I will try to estimate is Lo (2002).
> This is about the same as uplift modeling, uplift being another way of
> saying "proportional hazards modelling". For this analysis I have come
> across the Schoenfeld (1983), and the Stata program to estimate sample
> sizes, stpower (findit stpower). Unfortunately, I don't have access to
> Biometrics. So I am just guessing from the title that I am on the
> right track!
>
> Lo, V.S.Y. (2002) "The True Lift Model - A Novel Data Mining Approach
> to Response Modeling in Database Marketing." 4(2), p- 78-86.
>
> Schoenfeld, D. 1983. Sample-size formula for the proportional-hazards
> regression model. Biometrics 39: 499-503.
>
> Best wishes,
> Alexander
>
>
> -----Opprinnelig melding-----
> Fra: [email protected] [mailto:owner-
> [email protected]] P� vegne av Steven Samuels
> Sendt: 11. mai 2008 19:03
> Til: [email protected]
> Emne: Re: st: Control groups
>
> Alexander,
>
> Without more information, I cannot tell if -samnpsi- or any of the
> other programs that you tried will give you proper answers. They will
> be okay, for example, if 1) you measure responses without sampling or
> by simple random sampling; and 2) you don't intend to generalize your
> findings beyond the two particular populations you study. Different
> designs other than aimple two-group cross- sectional comparison might
> reduce the needed sample size and strengthen your conclusions.
> Whether your control group is internal (same
> population) or external (another population) matters, too.
>
> In any case, more details would be helpful.
>
> Steven
>
> On May 9, 2008, at 5:52 PM, <[email protected]>
> <[email protected]> wrote:
>
>> Dear Statalisters,
>>
>> Say I have a population of 500 000. I would like to treat this
>> population with some sort of communication, and to be able to measure
>> the effect of this treatment I have the opportunity to draw a control
>> group. Based on earlier experiences the effects between the treated
>> and the controlgroup could be as small as 0.5%.
>>
>> I want to be able to detect such a small effects, and I am wondering
>> how large my control groups ideally would be to track these changes,
>> say at an alpha level of 0.05.
>>
>> I have tried to use the fpower (findit fpower) and the simpower
>> (findit
>> simpower) to determine optimal control group sizes. I am curious
>> whether there are other alternatives in Stata?
>>
>> Thanks! And have a nice weekend.
>>
>> Best wishes,
>> Alexander
>>
>> *
>> * For searches and help try:
>> * http://www.stata.com/support/faqs/res/findit.html
>> * http://www.stata.com/support/statalist/faq
>> * http://www.ats.ucla.edu/stat/stata/
>
> *
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>
> *
> * For searches and help try:
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> * http://www.ats.ucla.edu/stat/stata/
*
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