Re: [R-sig-eco] Which function would fit these data (Version 2)

On 04/13/2012 06:16 AM, Beutel, Terry S wrote: Hi list members Sending this again as symbols in the previous version did not translate. Apologies if this is not too specifically R related, but I am looking fit a model to some simulated data. X is distance to sample point, y is binary outcome

Re: [R-sig-eco] ICC confidence intervals and power analysis for random effects in lmer?

On 04/13/2012 04:17 AM, Bradley Carlson wrote: Thanks for the tips everyone - I'll look into MCMC sampling for the CI. As far as the power analysis goes, I'm somewhat familiar with the criticisms regarding power analysis. I think this reviewer was curious about it because there was a small sample

[R-sig-eco] Which function would fit these data (Version 2)

Hi list members Sending this again as symbols in the previous version did not translate. Apologies if this is not too specifically R related, but I am looking fit a model to some simulated data. X is distance to sample point, y is binary outcome (present/absent). I was hoping someone can sugges

[R-sig-eco] Which function wiould fit these data?

Hi list members. Apologies if this is not too specifically R related, but I am looking fit a model to some simulated data. X is distance to sample point, y is binary outcome (present/absent). I was hoping someone can suggest a (presumably) non linear function that might meet the following criter

Re: [R-sig-eco] ICC confidence intervals and power analysis for random effects in lmer?

Thanks for the tips everyone - I'll look into MCMC sampling for the CI. As far as the power analysis goes, I'm somewhat familiar with the criticisms regarding power analysis. I think this reviewer was curious about it because there was a small sample size (small number of levels of the random effec

Re: [R-sig-eco] ICC confidence intervals and power analysis for random effects in lmer?

In addition to Bob O'Hara's suggestion, here is another citation you can give the reviewer/editor, as to why retrospective power analyses are a waste of time. Hoenig, J. M. and D. M. Heisey (2001). "The abuse of power: the pervasive fallacy of power calculations for data analysis." American S

Re: [R-sig-eco] ICC confidence intervals and power analysis for random effects in lmer?

> 2) A reviewer requested a power analysis of the ability to detect a > significant random effect. Any tips on how to approach that? The reviewer was requesting a post-hoc power analysis, either an 'observed power' or 'detectable effect size' analysis. Hoenig and Heisey (2001) provide the defi