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From |
Roger Newson <roger.newson@kcl.ac.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Sample size calculation |

Date |
Wed, 26 Oct 2005 17:09:21 +0100 |

My previous experience with cytokines is that (if measured well) they should have an approximately log-normal distribution. Therefore, to compare 2 groups of cytokine measurements, the correct approach is probably to define a confidence interval for a ratio of geometric means. To do power calculations for this, you need to know two main things, firstly the size of a clinically interesting geometric mean ratio to be detected, and secondly the likely within-group variability of the logs (which may be measured by coefficient of variation, SD of the logs, interpercentile ratio, or sometimes by geometric SD).

Power calculations for lognormally distributed variables are discussed in Newson (2004), which can be downloaded from my website (see my signature below) either using a browser or by typing within Stata

net describe powergen, from(http://www.kcl-phs.org.uk/rogernewson/papers)

and getting the ancillary file -powergen.pdf-. Geometric means and their ratios in Stata are discussed in Newson (2003), which can also be downloaded from my website either using a browser or typing within Stata

net describe gmratio, from(http://www.kcl-phs.org.uk/rogernewson/papers)

and getting the ancillary file -gmratio.pdf-. Another good source on the lognormal distribution is Stanislav Kolenikov's website at

http://www.komkon.org/~tacik/

which features a very useful reference with formulas at

http://www.komkon.org/~tacik/science/lognorm.pdf

I hope this helps.

Best wishes

Roger

References

Newson R. 2003. Stata tip 1: The eform() option of regress. The Stata Journal 3(4): 445. Also downloadable from my website at

http://www.kcl-phs.org.uk/rogernewson/

Newson R. 2004. Generalized power calculations for generalized linear models and more. The Stata Journal 4(4): 379-401. Also downloadable from my website at

http://www.kcl-phs.org.uk/rogernewson/

At 16:01 26/10/2005, Ronan wrote:

On 26 DFómh 2005, at 14:19, <slaowattana@pol.net> <slaowattana@pol.net> wrote:We are planning to measure some cytokines in patients with MS comparing between a group with treatment and control, but there have not been literatures regarding these measurements, so we do not have an estimated mean and standard deviation. Is there a way to estimate a sample size? (our IRB really wants to see sample size estimate.) Thanks.You really are in the dark, then. There are several approaches. The Resource Equation method http://embryo.ib.amwaw.edu.pl/invittox/er/ER/ER%2029.pdf see page 9 is useful in a preliminary experiment. It's based on the idea that the amount of information in each new piece of data diminishes as the sample size increases. It allows you to estimate the sample size needed to ascertain whether a study would be useful or not. It is often used in animal research where investigators have no idea at all of what they might find. Ronán Conroy rconroy@rcsi.ie * * 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/

-- Roger Newson Lecturer in Medical Statistics Department of Public Health Sciences Division of Asthma, Allergy and Lung Biology King's College London 5th Floor, Capital House 42 Weston Street London SE1 3QD United Kingdom Tel: 020 7848 6648 International +44 20 7848 6648 Fax: 020 7848 6620 International +44 20 7848 6620 or 020 7848 6605 International +44 20 7848 6605 Email: roger.newson@kcl.ac.uk Website: http://phs.kcl.ac.uk/rogernewson/ Opinions expressed are those of the author, not the institution. * * 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/

**References**:**st: Sample size calculation***From:*<slaowattana@pol.net>

**Re: st: Sample size calculation***From:*Ronán Conroy <rconroy@rcsi.ie>

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