similar to: How to obtain intercept statistics in anova with within-subject factors?

Dear R users,I am looking for an easy (i.e., direct) way in obtaining the F and p values from the intercept in anovas with within-subject designs. Data are from a psychophysics expeirment where I am using d' (d-prime) values obtained from 3 modalities of presentation in each subject.I would like to know not only whether there is an effect of modality, but also wether the main effect is

Dear R users: I have some difficulties analizing data with mixed effects NLME and the last version of R. More concretely, I have a repeated measures design with a single group and 2 experimental factors (say A and B) and my interest is to compare additive and nonadditive models. suj rv A B 1 s1 4 a1 b1 2 s1 5 a1 b2 3 s1 7 a1 b3 4 s1 1 a2

Hi, I'm trying to use the VLIWPacketizerList to schedule instructions for the R600 target, and I'm running into this assertion failure: ScheduleDAGInstrs.cpp:558: Cannot schedule terminators or labels! I think I might not be using the VLIWPacketizerList class correctly. I've attached my code to this email. Can anyone spot what I'm doing wrong? Also, I had to add a LiveIntervals

I am in the process of transferring from an old version of S+ to using R having used a variety of other packages in the past. I'm hugely impressed with R but it has an excellent but depressing habit of exposing that I'm not a professional statistician and has done so again. Someone has run a nice little repeated measures design on my advice, students randomised to four orders of a

So I have a system running: FreeBSD walk.dclg.ca 9.2-RC3 FreeBSD 9.2-RC3 # r254952: Wed Aug 28 03:02:55 EDT 2013 root at walk.dclg.ca:/usr/obj/usr/src/sys/STRIKE i386 and it has two 2T SATA disks. To keep this post short, the crash.txt is here. https://uk.eicat.ca/owncloud/public.php?service=files&t=fea9d25579fe0c4afb808859e80e1493 now curiously, while running a "make -j4

Sure I will split it and put it in two patches. Give me few hours. I need to test those patches. Sirish On 4/19/2012 8:40 AM, Tom Stellard wrote: > On Wed, Apr 18, 2012 at 11:18:05PM -0500, Sirish Pande wrote: >> Hi, >> >> Here's a patch for Hexagon Packetizer for review. This patch does >> not yield any warnings. >> > Would it be possible to split this

Dear advanced statisticians, *******Objectif******** I try to set up linear models with mean as intercept: Answer: y Variable: x, as factor of two modalities: x(1), x(2). I would like to have a model as: y = mean(y)+A(i)+residuals, with i in (1,2) and A(1) coefficient for x(1) and A(2) coefficient for x(2). *******Trials in R******* ## Firstly: I write in R: >Model<-lm(y~x,Data)

Hi! Can anyone tell me how to convert the anova/ancova summary output into a data frame? Thanks! Shane Phillips [[alternative HTML version deleted]]

Hi, I want to fit some psychophysical data with cumulative gaussians. There is quite a convenient toolbox for matlab called 'psignifit' (formerly known as 'psychofit'). It allows the lower bound of the sigmoid to vary slightly from zero, aswell as the upper bound to vary from one. with these two free parameters, the fitted function is less sensitive to noisy data and outliers.

Hello, I have not had much time to research this problem yet, so please let me know what further information I might be able to provide. This weekend I attempted to upgrade a computer from 8.2-RELEASE-p3 to 8.4 using freebsd-update. After I rebooted to test the new kernel, I got a panic. I had to take a picture of the screen. Here's a condensed version: panic: page fault cpuid = 1 KDB:

Dear Friends, I not sure whether this is an Sweave or a beamer problem. The Rnw file: \documentclass[compress,smaller]{beamer} %\documentclass{article} %\usepackage{beamerarticle} \usepackage{Sweave} \title{Psychophysics II} \date{September 9, 2008} \begin{document} \frame{ \begin{Schunk} \begin{Sinput} > ro <- 0.2 > c <- seq(from = -3, to = 4, by = 0.1) > fn <- 1 -

Dear list, I hope the topic is of sufficient interest, because it is not R-related. I have N=100 yes/no-responses from a psychophysics paradigm (say Y Yes and 100-Y No-Responses). I want to see whether these yes-no-responses are in line with a model predicting a certain amount p of yes-responses. Standard procedure would be a one-sample binomial test for the observed proportion, chi?(1 df) =

Dear R-Experts, I was wondering how to fit a cumulative gaussian to a set of empirical data using R. On the R website as well as in the mail archives, I found a lot of help on how to fit a normal density function to empirical data, but unfortunately no advice on how to obtain reasonable estimates of m and sd for a gaussian ogive function. Specifically, I have data from a psychometric function

I need to use Alt-F2 shortcut in Far Manager running with wineconsole. But Alt-F2 invokes standard Linux "run command" dialog. How can I intercept the Alt-F2 so that it is processed by Wine application?

I realize that the following has been talked about on this list many times before in some related way but I am going to ask for help anyway because I still don't know what to do. Suppose I have no intercept models such as the following : Y = B*X_1 + error Y = B*X_2 + error Y = B*X_3 + error Y = B*X_4 + error and I run regressions on each ( over the same sample of Y ) and now I want to

Hi all, Dear Dr. Wheeler, I am trying to use the lmPerm package to perform multiple regression on microarray data with certain empirical variables associated with treatments of the experiment. In order the circumvent the very conservative multiple test corrections such as Bonferroni and BH, I try to use permutated probabilities to assess associations. In addition to mu previous posting I

Hello, I'm implementing a function using non uniform B-Splines. Looking at the code of the bs() function, I realized that if the intercept was set to FALSE, the behavior of the function was the following (df is the number of degrees of freedom that I believe can be interpreted as the number of control points): - Compute df- ord + 1 _internal_ knots (ord is the order of the spline) - Add ord

Dear list, I'm trying to fit a glm model using family=poisson(link = "identity"). The problem is that the glm function fits a model with a negative intercept, which sounds like a nonsense to me, being the response a Poisson variable. >From a previous discussion on this list I've understood that the glm function uses IRLS for the fitting without any constraint so it is

It's easy to run a linear regression on a simple model without an intercept just by doing this: lm(y ~ x1 + x2 -1) Is there a similar trick to suppress the intercept when your model is in a large dataframe and you don't want to write out the names of individual columns? -- View this message in context:

I would appreciate if someone could tell me how to fit a non-intercept model using lrm (and not glm). The -1 in the formula of the glm does not work with lrm. Thanks, Clarissa [[alternative HTML version deleted]]