Re: [R] Omnibus main effects in summary.lme?

From: Andrew Beckerman <a.beckerman_at_sheffield.ac.uk>
Date: Thu, 10 Jan 2008 23:42:36 +0000

Adam -

Without resorting to the rather rich lmer/lme4 discussion realm, you need to base anova() comparisons of lme models with different fixed effects on maximum liklihood estimates rather tham REML.

anova(update(l2,method="ML"),update(l2,~.-useful:nusience,method="ML"))

should avoid the error and give a conservative estimate of the significance of your interaction.

see also:
http://tolstoy.newcastle.edu.au/R/e2/help/06/10/3565.html

and related posts.

A



Dr. Andrew Beckerman
Department of Animal and Plant Sciences, University of Sheffield, Alfred Denny Building, Western Bank, Sheffield S10 2TN, UK ph +44 (0)114 222 0026; fx +44 (0)114 222 0002 http://www.beckslab.staff.shef.ac.uk/

On 10 Jan 2008, at 22:32, Adam D. I. Kramer wrote:

> Hello,
>
> I've been running some HLMs using the lme function quite happily; it
> does what I want and I'm pretty sure I understand it.
>
> The issue is that I'm currently trying to estimate a model with a
> 14-level "nusiance" factor as an independent variable...which makes
> the
> output quite ugly. All I'm really interested in is the question of
> whether
> these factor as a whole (and its interactions with other factors) are
> significant.
>
> The summary.aov function provides this sort of aggregation for lm
> objects, but does not run on lme objects. I've also tried estimating
> the
> full model and restricted model, leaving out a main effect or
> interaction
> term and then using anova.lme to compare the models, but these
> models appear
> to be being fit differently. Say I have l2, and then
>
> l3 <- update(l2, .~.-useful:nusience)
> anova.lme(l3,l2)
>
> ...to see whether the interaction term is significant, produces the
> error,
> "Fitted objects with different fixed effects. REML comparisons are not
> meaningful." Upon examination using summary(l3), it seems that the
> fixed
> factors are indeed different.
>
> So, my question is this: How do I estimate omnibus main effects for
> multi-level factors and multi-level factor interactions in lme models?
>
> Many thanks,
> Adam D. I. Kramer
> Ph.D. Student, Social and Personality Psychology
> University of Oregon
>
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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 10 Jan 2008 - 23:46:08 GMT

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