[R-sig-ME] Logit mixed model power analysis

Andrew Robinson A.Robinson at ms.unimelb.edu.au
Wed Sep 16 03:44:01 CEST 2015

I understand post-hoc power as being a function of the p-value, and
therefore redundant.  When asked for the kind of information that post-hoc
power is used to represent, I prefer to provide confidence intervals on the
parameters of interest - if possible.

Best wishes,


On Wed, Sep 16, 2015 at 11:29 AM, David Duffy <
David.Duffy at qimrberghofer.edu.au> wrote:

> On Wed, 16 Sep 2015, Paul Johnson wrote:
> I second what Thierry said about the pointlessness of post-hoc power
>> analysis when using the observed effect size.
>>> Post-hoc power tests are not very informative. You will get a high
>>> power when the signal is significant and low power when not
>>> significant.
> A few people defend it as an estimate of the reproducibility probability.
> Gelman and Carlin suggest plugging in a "sensible" (Bayesian) estimate of
> the true effect based on your prior knowledge, so you can estimate the
> probability of a "Type S" (sign of true effect could actually be opposite
> to your study point estimate) or "Type M" error.
> Cheers, David.
> | David Duffy (MBBS PhD)
> | email: David.Duffy at qimrberghofer.edu.au  ph: INT+61+7+3362-0217 fax:
> -0101
> | Genetic Epidemiology, QIMR Berghofer Institute of Medical Research
> | 300 Herston Rd, Brisbane, Queensland 4006, Australia  GPG 4D0B994A
> _______________________________________________
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Andrew Robinson
Deputy Director, CEBRA, School of Biosciences
Reader & Associate Professor in Applied Statistics  Tel: (+61) 0403 138 955
School of Mathematics and Statistics                        Fax: +61-3-8344
University of Melbourne, VIC 3010 Australia
Email: a.robinson at ms.unimelb.edu.au
Website: http://www.ms.unimelb.edu.au/~andrewpr

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