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From |
"Joseph Coveney" <stajc2@gmail.com> |

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

Subject |
st: Re: which statistical analysis to evaluate vitals signs |

Date |
Tue, 11 Feb 2014 17:20:32 +0900 |

Dao Kim wrote: Hi, which statistical analysis would you use to analyse tolerance to a drug, for evaluation of blood pressure, oxygen saturation, pulsation before and after a drug, to detect a 10% difference between both values? -------------------------------------------------------------------------------- Because your description calls for only a single administration, I'm guessing that you meant drug tolerability (absence of side effects) and not drug tolerance (attenuation of effects upon repeated exposure). How about MANOVA? You could then jointly test for a difference in before-and-after change scores for each of the three vital signs. The null hypothesis would be that the absolute value of the mean change score for at least one of them exceeds 10% (you'll need to decide the denominator for that), that is, the drug has poor tolerability. The alternative hypothesis would then be that none of the absolute values of the three mean change scores exceeds 10%, that is, the drug at the examined dose level has good tolerability in terms of the three vital signs. (You would construct joint 90% confidence intervals and interpret them just as in a therapeutic equivalence--a.k.a., bio-equivalence--study.) Power analysis could be by simulation (readily done in Stata) using whatever you've got now on correlation structure. You'd need to look into how well the underlying assumptions for MANOVA hold up, and you might need to consider transforming the oximeter measurements, but, again, it would allow for joint testing of hypotheses for the correlated data. . . . should be at least worth suggesting to your site's biostatistician. Joseph Coveney * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: which statistical analysis to evaluate vitals signs***From:*Dao Kim <Kim.Dao@chuv.ch>

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