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...way to work around this? Ultimately I'd like to make multiple graphs by looping throught the values in vectors. Something like: > var<-c(var1,var2...n) > for (v in var) >{ > plot(var, x)) >} I've looked around for help on this but am stuck. Hope you can help, Gijs Plomp

...le to make an informed guess on the likely impact. Use of simulate.lme() seems like a good idea. John Maindonald. On 11 Aug 2004, at 8:05 PM, r-help-request at stat.math.ethz.ch wrote: > From: Spencer Graves <spencer.graves at pdf.com> > Date: 10 August 2004 8:44:20 PM > To: Gijs Plomp <gplomp at brain.riken.jp> > Cc: r-help at stat.math.ethz.ch > Subject: Re: [R] Enduring LME confusion.... or Psychologists and > Mixed-Effects > > > Have you considered trying a Monte Carlo? The significance > probabilities for unbalanced anovas use approximation...

...y: is anyone planning a lenny-cran? If not, can I help (I've only got amd64/x86_64 systems available)? I'll need some help setting things up; currenlty I've got one system running lenny (without R as you'll have understood) on which I could try to compile R packages. Yours, Piet Plomp

Dear ExpeRts, Suppose I have a typical psychological experiment that is a within-subjects design with multiple crossed variables and a continuous response variable. Subjects are considered a random effect. So I could model > aov1 <- aov(resp~fact1*fact2+Error(subj/(fact1*fact2)) However, this only holds for orthogonal designs with equal numbers of observation and no missing values.

Announcing cran2deb: 1700+ Debian packages from almost all of CRAN ------------------------------------------------------------------ Last Friday's presentation at UseR! 2009 was the first really public mention of 'cran2deb'. It provides Debian packages of all of CRAN. It started as Charles' project from last year's Google Summer of Code, was further extended by us over the