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From |
"Svend Juul" <SJ@SOCI.AU.DK> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Power calculation and sample sizes |

Date |
Fri, 17 Aug 2007 14:03:56 +0200 |

Cecilia wrote: I would like to determine the sample size for a RCT. Control and intervention groups will have the same size. The intention of the intervention is to increase a certain preventive measure among patients. We will measure prevalence of the preventive measure at baseline for both groups and expect to find that 20% of all the patients (control and intervention) adopt the measure before the experiment. We would like to be able to detect a change from 20% to 40% in the intervention group, while we expect that the control group will change their adoption rates from 20% to 25%. My first plan was to simulate some samples, starting with some hypothetical sample size, then run a logistic model multiple times, and calculate power as a proportion of times when the expected coeficients were significant. Then repeat the simulations for different sample sizes until I could had an idea of sample size versus power. ------------------------------------------------------------------- -search sample size- points, among other things, to the official Stata command -sampsi-. A change from 20% to 40% means an increase of 25% among the 80% non-adopters at baseline, and a change from 20% to 25 % means an increase of 6.25%. The command now is: . sampsi .25 .0625 Estimated sample size for two-sample comparison of proportions Test Ho: p1 = p2, where p1 is the proportion in population 1 and p2 is the proportion in population 2 Assumptions: alpha = 0.0500 (two-sided) power = 0.9000 p1 = 0.2500 p2 = 0.0625 n2/n1 = 1.00 Estimated required sample sizes: n1 = 88 n2 = 88 Now, the 88 + 88 are the numbers for 80% non-adopters at baseline, so you should add 25% to these figures, i.e. 110 + 110. - if you want alpha=0.05 and power=0.90. Hope this helps Svend __________________________________________ Svend Juul Institut for Folkesundhed, Afdeling for Epidemiologi (Institute of Public Health, Department of Epidemiology) Vennelyst Boulevard 6 DK-8000 Aarhus C, Denmark Phone: +45 8942 6090 Home: +45 8693 7796 Email: sj@soci.au.dk __________________________________________ * * 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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