[R-sig-ME] prediction intervals from a mixed-effects models?
reinhold.kliegl at gmail.com
Mon Apr 14 09:41:29 CEST 2008
I think the Gelman & Hill (2007) book has examples that look less
complicated to me in comparison to what you describe (i.e. simply
sample from the estimated distributions). I have some code for
computation of power, also following examples in this book. Perhaps, I
am overlooking something.
On Sun, Apr 13, 2008 at 7:10 PM, Spencer Graves <spencer.graves at pdf.com> wrote:
> How can I get prediction intervals from a mixed-effects model?
> Consider the following example:
> fm3 <- lme(distance ~ age*Sex, data = Orthodont, random = ~ 1)
> df3.1 <- with(Orthodont, data.frame(age=seq(5, 20, 5),
> Subject=rep(Subject, 4),
> Sex=rep(Sex, 4)))
> predict(fm3, df3.1, interval='prediction')
> # M01 M01 M01 M01
> # 22.69012 26.61199 30.53387 34.45574
> # NOTE: The 'interval' argument to the 'predict' function was ignored.
> # It works works for an 'lm' object, but not an 'lme' object.
> One way to do this might be via mcmcsamp of the corresponding
> 'lmer' model:
> samp3r <- mcmcsamp(fm3r, n=10000)
> Then use library(coda) to check convergence and write a function
> to simulate a single observation from each set of simulated parameters
> and compute quantile(..., c(.025, .975)) for each prediction level
> However, before I coded that, I thought I would ask if some easier
> method might be available.
> p.s. RSiteSearch("lme prediction intervals") produced 3 hits including
> 2 from James A Rogers over 3 years ago. In one, he said, "I am not
> aware of any published R function that gives you prediction intervals or
> tolerance intervals for lme models."
> (http://finzi.psych.upenn.edu/R/Rhelp02a/archive/42781.html) In the
> other, he provided sample code for prediction or tolerance intervals of
> lme variance components.
> R-sig-mixed-models at r-project.org mailing list
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