Logit mixed model power analysis
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