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Re: st: Computing effect size for a clustered randomized control trial


From   Steve Samuels <sjsamuels@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Computing effect size for a clustered randomized control trial
Date   Mon, 3 May 2010 22:31:29 -0400

I should have looked at the subject of Joe's post.  He does say that
it is a "cluster-randomized trial".

Steve

On Mon, May 3, 2010 at 9:59 PM, Steve Samuels <sjsamuels@gmail.com> wrote:
> Joe's description of his design is vague.  He did not say whether the
> unit of randomization will be the classroom or thestudent (with
> classrooms as experimental blocks); nor whether the intervention will
> be applied to students in groups or individually.
>
> Steve
>
> On Mon, May 3, 2010 at 9:30 PM, Michael Norman Mitchell
> <Michael.Norman.Mitchell@gmail.com> wrote:
>> Greetings
>>
>>  I concur with Scott, that Optimal Design is very useful in this kind of
>> situation. I would especially recommend taking time with the user manual for
>> this program. The program is super well designed and easy to use, and I
>> think it is very tempting just to use the program without the documentation.
>> However, I feel that is cheating oneself because the manual is exceptional
>> in the way that it explains the underlying issues and how to conceptualize
>> them in terms of using their software. I think the trickiest bit, in your
>> case, will be the combination of the clustering and the repeated measures. I
>> think you will get the most mileage out of conceptualizing the "pre test" as
>> a level 1 covariate and I believe the optimal design software will permit
>> this. However, as the manual describes, it is "level 2" covariates that will
>> have the biggest impact on power. If the software does not support level 1
>> covariates in such a model, I don't think it will alter the power estimate
>> that much.
>>
>> I hope that is useful additional information.
>>
>> Michael N. Mitchell
>> See the Stata tidbit of the week at...
>> http://www.MichaelNormanMitchell.com
>>
>> On 2010-05-03 6.08 PM, Scott Baldwin wrote:
>>>
>>> I'm not aware of any built in or user-written method in Stata for
>>> computing power in cluster randomized trials. You can try the Optimal
>>> Design software
>>> (http://sitemaker.umich.edu/group-based/optimal_design_software) or
>>> the formulae in David Murray's book "Design and analysis of group
>>> randomized trials."
>>>
>>> Best,
>>> Scott
>>>
>>>
>>> On Mon, May 3, 2010 at 5:23 PM, Joe McCrary<joe.mccrary@gmail.com>  wrote:
>>>
>>>>
>>>> I am designing a randomized control trial, where we are going to
>>>> select about 12 students per classroom and randomize them into 3
>>>> groups, a control and 2 treatment groups. Is there a way I can compute
>>>> the number of classrooms needed for the study using the following
>>>> criteria:
>>>>
>>>> Desired power=0.8
>>>> Estimated effect size = 0.2
>>>> alpha = 0.0167
>>>> 1 pre-test measure
>>>> 1 post-test measure
>>>> approx correlation between the two measures = 0.25
>>>>
>>>> --
>>>> Joe McCrary
>>>> Senior Research Associate
>>>> WestEd-Atlanta
>>>> 260 Peachtree St., Suite 2200
>>>> Atlanta, GA 30303
>>>>
>>>> ph: 541-782-8626
>>>> fax: 404-393-3797
>>>>
>>>> Skype: joe.mccrary
>>>> Google talk; joe.mccrary
>>>> **********************
>>>>
>>>> "No problem can be solved from the same level of consciousness that
>>>> created it."
>>>> --Albert Einstein
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>
>
>
> --
> Steven Samuels
> sjsamuels@gmail.com
> 18 Cantine's Island
> Saugerties NY 12477
> USA
> Voice: 845-246-0774
> Fax:    206-202-4783
>



-- 
Steven Samuels
sjsamuels@gmail.com
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax:    206-202-4783

*
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