Re: SV: st: Control groups

[Steven Samuels <sjhsamuels@earthlink.net>]

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, <Alexander.Severinsen@telenor.com>  
<Alexander.Severinsen@telenor.com> 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: owner-statalist@hsphsun2.harvard.edu [mailto:owner- 
> statalist@hsphsun2.harvard.edu] P� vegne av Steven Samuels
> Sendt: 11. mai 2008 19:03
> Til: statalist@hsphsun2.harvard.edu
> 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, <Alexander.Severinsen@telenor.com>
> <Alexander.Severinsen@telenor.com> 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
> >
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