John D asked: > Given that things have been quiet in the list lately, I think this > could be a good time for me to ask your opinion about this issue. > > Imagine that I run a PIC analysis on two traits using 1000 > post-burn-in trees. What would be the best way to summarize these > results? Average p-values across all analyses? Perhaps a specific > method to combine the resulting probabilities e.g. Fisher's test?
If you want to know about a regression coefficient, or other parameter, the 1000 inferred values in the 1000 trees can be taken as a posterior distribution if the trees come from a Bayesian inference (I am assuming from your description that they do). If you want to test whether, say, the regression coefficient is positive, you can take this posterior distribution and simply ask whether the credible interval for the parameter includes zero. In this case that interval would be the upper 95% of the sample values. Bringing in P values or Fisher's test just mixes Bayesian with frequentist or likelihood methods, which will get two groups of people annoyed at you, whereas using only one of these methods has the advantage of irritating only one group of us. I note that John's email address is "dobzhanski". Good to hear from you again, Professor Dobzhansky. You may recall that you gave me a tour of your lab at Rockefeller University in the summer of 1963 when Dick Lewontin sent me from Rochester to pick up some data paperwork for him for a joint project the two of you were working on. (Okay, the last part is "Poisson d'Avrile") ---- Joe Felsenstein, [email protected] Dept. of Genome Sciences, Univ. of Washington Box 355065, Seattle, WA 98195-5065 USA _______________________________________________ R-sig-phylo mailing list - [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://www.mail-archive.com/[email protected]/
