similar to: Bootstrapping Contrasts for Repeated Measures ANOVA

Hi Folks, I have repeated measures for data on association time (under 2 acoustic condtions) in male and female frogs as they grow to adulthood (6 timepoints). Thus, two within-subject variables (Acoustic Condition: 2 levels, Timepoint: 6 levels) and one between-subject variable (Sex:male or female). I am pretty sure my distributions depart from normality but I would first like to simply run a

I am executing a Repeated Measures Analysis of Variance with 1 DV (LOCOMOTOR RESPONSE), 2 Within-Subjects Factors (AGE, ACOUSTIC CONDITION), and 1 Between-Subjects Factor (SEX). Does anyone know whether the between-subjects factor (SEX) belongs in the Error Term of the aov or not? And if it does belong, where in the Error Term does it go? The 3 possible scenarios are listed below: e.g., 1.

Hello list, I'm trying to figure out how exactly the specification of nested random effects works in the lmer function of lme4. To give a concrete example, consider the rat-liver dataset from the R book (rats.txt from: http://www.bio.ic.ac.uk/research/mjcraw/therbook/data/ ). Crawley suggests to analyze this data in the following way: library(lme4) attach(rats) Treatment <-

I have a server that runs stand-alone with an LDAP directory and a KDC . The linux machines have sssd to allow unified users etc. The clients are mostly MacOS and Windows machines that aren't part of an AD. This config has worked for 15 years, but after upgrading Debian and bringing in Samba Version 4.17.7-Debian it seems to be broken. I believe this is related to:

Can anyone using PAM and rsa-rhosts authentication replicate this? Damien -------------- next part -------------- An embedded message was scrubbed... From: Adrian Baugh <adrian at merlin.keble.ox.ac.uk> Subject: Serious Bug Report: OpenSSH Date: Wed, 1 Dec 1999 02:38:56 +0000 (GMT) Size: 3926 Url:

I am helping my wife do some statistical analysis. She is a biologist, and she has performed some measurements on various genotypes of mice. My background is in applied mathematics and engineering, and I have a fairly good statistics background, but I am by no means a PhD level expert in statistical methods. We have used the lmer package to fit various models for the various experiments that she

[Yes, this is related to a homework problem, but is not the problems itself.] In my mathematical statistics class, we've just learned about properties of estimators, and I can now solve manually problems like this: A sample of size n = 16 is drawn from a normal distribution where sigma = 10 but mu is unknown. If mu = 20, what is the probability that the estimator mu hat = Y bar will lie

Please note clarifications in <<>> below. My apologies for any confusion. Thanks again, Scott ---------- Forwarded message ---------- From: Scott Stark <stark.sc@gmail.com> Date: Aug 23, 2007 1:03 PM Subject: Expedite scalar f(x) evaluation over vectors To: r-help@lists.r-project.org Dear R community, I am trying to code a fairly complex equation for optim(). My current

Hi! I'm translating some code from Matlab to R and I found a problem. I need to translate Matlab's function 'lsqnonlin' (http://www-ccs.ucsd.edu/matlab/toolbox/optim/lsqnonlin.html) into R, and at the beginning I thought it would be the same as R's 'optim'. But then I looked at the definition of 'lsqnonlin' and I don't quite see how to make

Folks, I wonder if anything could be said about the distribution of a random variate x, where x = N(0,1)/N(0,1) Obviously x is pathological because it could be 0/0. If we exclude this point, so the set is {x/(0/0)}, does x have a well defined distribution? or does it exist a distribution that approximates x. (The case could be generalized of course to N(mu1, sigma1)/N(mu2, sigma2) and one

Hi, New to R, I don't find a way to plot the following data with image(): x is a N * M matrix y is a vector of length M z is a N*M matrix I wish to plot z as a greyscale image, but my x axis is different for every row of the z data. Here is a minimal example, > theta<-c(3:6) # N > y<-c(1:5) # M > > x<-theta%*%t(y)# N * M > z<-sin(x) # N * M > > image(z)

Dear All, Is there any package to do multi-objective optimization? For instance, consider the following problem: maximize f(x,y) in order to x and maximize g(x,y) in order to y, simultaneously, with x and y being the same both for f and g. Can R do it numerically? Thanks in advance, Paul

I am a SAS user currently evaluating R as a possible addition or even replacement for SAS. The difficulty I have come across straight away is R's apparent difficulty in handling relatively large data files. Whilst I would not expect it to handle datasets with millions of records, I still really need to be able to work with dataset with 100,000+ records and 100+ variables. Yet, when reading

Hello: I am using R mainly on windows XP, version 2.5. I?m a biologist, with a medium level statistics background. I have a problem stating a two-way factorial design where both factors are random. I?m using the lmer() function implemented in the Matrix package version 0.99. My design is as follows: Two species were randomly selected from a total of 4 species. This species are present

I have 316 files. Each file represents a patient's breathing track (respiratory signal recorded for a variable number of cycles). All files have the same are made up of a header followed by a variable number of records. Each record contains 7 comma separated fields. The patient ID is recorder in the header which is stripped off when reading the file into a R data.frame. Since I need to keep

Dear All, I know how to export graphics as pdf files and then how to include them in LaTeX documents. However, I do not know how to do in order to have the text of the graphics written with the font selected for the LaTeX document. Is that possible? Thanks in advance, Paul

Hello, We?re receiving reports of extremely slow rendering by users who are using the new geom_sf() feature in ggplot2. Importantly, this seems to be a graphics device issue, because the exact same plot takes vastly different amounts of time to render under different devices. We?re talking about 2 seconds vs. 100 seconds here, so not a small effect. In particular, the quartz device on OS X seems

I have some code that calls R's finalizer interface, e.g., .Call('R_RegisterFinalizerEx', object, function, TRUE) This worked pre 1.6, but now I get '.Call function name not in call table'. Are functions listed in Rinternals.h no longer available in .Call? Or is this a namespace issue? How do I reference the function? Thanks. Tim -- Timothy H. Keitt The University of

Hello, I asked this question a little while ago ( https://stat.ethz.ch/pipermail/r-help/2008-April/158761.html ) but got no response. Can anybody explain to me the difference between /, :, and %in% in the definition of random effects in lmer, such as: (1|A/B), (1|A:B), (1|B %in% A)? My understanding is that (1|A/B) is the same as (1|A) + (1|A:B), but I have not seen this stated explicitly

I'm looking for a function in R similar to t.test() which was generously pointed out to me yesterday, but which can be used for normally distributed data. To recap yesterday: > x <- scan() 1: 62 52 68 23 34 45 27 42 83 56 40 12: Read 11 items > alpha<- .05 > t.test(x) One Sample t-test data: x t = 8.8696, df = 10, p-value = 4.717e-06 alternative hypothesis: true