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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Tue, 4 May 2010 13:12:02 -0400 |

Joe McCrary <joe.mccrary@gmail.com>: I realize I'm coming to this discussion late, but can't you just invert a formula like Equation 21 on page 17 of http://www.mdrc.org/publications/437/full.pdf to get the estimated required sample size J for an MDES of .2 with an n of 12, a fraction P in the treatment group of 1/3, an ICC of about .1 (say) and an R1 of about .25 like so: . di ceil(2.8^2/(.2^2*1/3*(1-1/3))*(.1+.9*(.75)/12)) 138 i.e. about 140 classrooms (with 12 students apiece)? Also illustrates the advantage of including classroom-level covariates (via parameter R2, assumed to be .5 below): . di ceil(2.8^2/(.2^2*1/3*(1-1/3))*(.1*.5+.9*(.75)/12)) 94 I note in passing that .2 is a very large effect; probably you want MDES=.1 or even .05 or smaller, even if you think the true effect is really .2 On Mon, May 3, 2010 at 7:23 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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Computing effect size for a clustered randomized control trial***From:*Joe McCrary <joe.mccrary@gmail.com>

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