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8 results for “from:Brad Buchsbaum”

coding factor replicates
Brad Buchsbaum · Jan 23, 2002 · r-help

Hi All, If I have a factor f: A B C B C A C B A A B .... and I would like to generate a factor to indicate the trial number as a function of condition: e.g. 1...

overlapping repeated measures
Brad Buchsbaum · Jun 14, 2002 · r-help

Hi, Is there a library in R that could be used to estimate the temporal profile for a factor (time) whose levels overlap, e.g. t1 t2 t3 t4 t5 t6 t7 t8 t1 t2 t3 t4 t5 t6 t7...

contrasts with aov
Brad Buchsbaum · Jul 1, 2002 · r-help

Hi all, I'd like to carry out what amounts to a succession of paired t-tests across units in a repeated measures design. I thought I could accomplish this using aov with an Error argument and the contr.sdif...

variable argument lists
Brad Buchsbaum · Apr 2, 2002 · r-help

Hi, Is it possible to make a function treat an R list as if it were a sequence arguments? For instance, the "order" function has a variable length argument list. So one could do: x <- order(a,b) Suppose one...

coding factor replicates
Brad Buchsbaum · Jan 23, 2002 · r-help

On Wednesday 23 January 2002 02:11 pm, Uwe Ligges wrote: > Brad Buchsbaum wrote: > > Hi All, > > > > If I have a factor f: > > > > A B C B C A C B A A B .... > > > > and I would like to generate a...

trellis plot
Brad Buchsbaum · Nov 28, 2001 · r-help

Hi, I'd like to plot 4 groups of data using xyplot and panel.superpose so that the points are overlayed on a single plot. For each group of data I'd also like a loess smoothed function (using panel...

SJava.dll, UnsatisfiedLinkError
Brad Buchsbaum · Aug 14, 2002 · r-help

Pauline, Notice your path is separated by colons, and you seem to be using windows. Brad Buchsbaum On Wed, 14 Aug 2002, Pauline Gu wrote: > Dear R experts and Omega experts, > > I am trying to run the R from Java...

nested versus crossed random effects
Brad Buchsbaum · Jan 24, 2002 · r-help

Hi all, I'm trying to test a repeated measures model with random effects using the nlme library. Suppose I have two within subjects factors A, B both with two levels. Using aov I can do: aov.1 <- aov(y...

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