similar to: Random effects ANOVA?

Dear all, I am having quite a hard time in trying to figure out how to correctly spell out a model in R (a repeated-measures anova with a within-subject covariate, I guess). Even though I have read in the posting guide that statistical advice may or may not get an answer on this list, I decided to try it anyway, hoping not to incur in somebody's ire for misusing the tool. For the sake of

Hi all -- I have to calculate a likelihood ratio test for a logit model. I found logLik, but I need to calculate the log likelihood for the model without any predictors. How can I specify this in glm? If the full model is glm(y ~ x1), is the one without predictors (y ~ 0)? Or (y ~ 1)? Is there a more direct way of getting this? -- Chris

Hi all I am running a 2-way repeated measure anova with 1 between-subjects factor (Group=treatment, control), and 1 within-subject factor (Time of measurement: time1, time2). I extract the results of the anova with: summary(aov(effect ~ Group*Time + Error=Subj/Time, data=mydata)) Now, this must be clearly a dumb question, but how can I quickly extract in R all the post-hoc t-tests for the

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.

Hi all -- So I'm working through my statistics homework again, and trying to reproduce the examples in the book (Kirk's _Experimental Design_, third edition) in R. This is a completely randomized hierarchical design (CRH-28(A)). The B factor is completely nested within the A factor. Pages 480-482, for those playing along at home. I can use: summary(aov(value ~ a + Error(b),

I have 2 questions on ANOVA with 1 between subjects factor and 2 within factors. 1. I am confused on how to do the analysis with aov because I have seen two examples on the web with different solutions. a) Jon Baron (http://www.psych.upenn.edu/~baron/rpsych/rpsych.html) does 6.8.5 Example 5: Stevens pp. 468 - 474 (one between, two within) between: gp within: drug, dose aov(effect ~ gp * drug *

Hi everyone, I am fairly new to R, and I am aware that others have had this problem before, but I have failed to solve the problem from previous replies I found in the archives. As this is such a standard procedure in psychological science, there must be an elegant solution to this...I think. I would much appreciate a solution that even I could understand... ;-) Now, I want to calculate a

Hi I am attempting Anova analysis to compare results from four groups (Samp1-4) which are lists of intensities from the experiment. I am doing this by first creating a structured list of the data and then conducting the ANOVA (Script provided below). Im an R beginner so am not sure if I am using this correctly. Two major questions I have are: 1) Is using the code (zzz.aov <- aov(Intensity ~

I've tried without success to calculate interaction and main effects contrasts using R. I've found the functions C(), contrasts(), se.contrasts() and fit.contrasts() in package gmodels. Given the url for a small dataset and the two-way anova model below, I'd like to reproduce the results from appended SAS code. Thanks. --Dale. ## the dataset (from Montgomery) twoway <-

Dear R-list members, I've been struggling with the proper setup for analysing my data. I've performed a route choice experiment, in which participants had to make a choice at each junction for the next road. During the experiment they received traffic information, but also encountered two different accidents. They also made trips without accidents. What I'm interested in is to

Hi I have data from 12 subjects. The measurement is log(expression) of a particular gene and can be assumed to be normally distributed. The 12 subjects are divided into the following groups: Infected, Vaccinated, Lesions - 3 measurements Infected, Vaccintaed, No Lesions - 2 measurements Infected, Not Vaccinated, Lesions - 4 measurements Uninfected, Not Vaccinated, No Lesions - 3 measurements

Dear R users, I have copied for following table from an article on "Using confidence intervals in within-subject designs": Subject 1sec 2sec 5sec 1 10 13 13 12.00 2 6 8 8 7.33 3 11 14 14 13.00 4 22 23 25 23.33 5 16 18 20 18.00 6 15 17 17 16.33 7 1 1 4 2.00 8 12 15 17 14.67 9 9 12 12 11.00 10 8 9 12 9.67 I rearranged the data this way:

Hallo! I have data of the following design: NSubj were measured at Baseline (visit 1) and at 3 following time points (visit 2, visit 3, visit 4). There is or is not a treatment. Most interesting is the question if there is a difference in treatment between the results of visit 4 and baseline. (The other time points are also of interest.) The level of significance is alpha=0.0179 (because of an

Hi, I have sort of a newbie question. I've seriously put a lot of effort into how to handle simple replicates in a repeated ANOVA design, but haven't had much luck. I really liked reading "Notes on the use of R for psychology experiments and questionnaires", by Jonathan Baron and Yuelin Li ( http://www.psych.upenn.edu/~baron/rpsych/rpsych.html ) but still didn't run across

> On 30/10/2020 19:25 Bernd Petrovitsch <bernd at petrovitsch.priv.at> wrote: > > > On 30/10/2020 17:11, @lbutlr wrote: > [...] > > echo $1 | sed -e '|</head>|<style>* {color:white !important; background-color: black !important; } </style></head>|' > > What should the sed stuff do? > TTBOMK '|' is not known by sed ...

Dear all, I am unsure about how to specify a model in R and I thought of asking some advice to the list. I have two groups ("Group"= A, B) of subjects, with each subject undertaking a test before and after a certain treatment ("Time"= pre, post). Additionally, I want to enter the age of the subject as a covariate (the performance on the test is affected by age),

On Sun, 10 Oct 2004, RenE J.V. Bertin wrote: > Could I ask some hints/help in interpreting the following ANOVA results, > please? This concerns an experiment where I study the incidence and > severity of motion sickness. I have Sickness.norm, a subjective > discomfort/sickness estimate, normalised to 0..1, the session time T > (normalised to 0..1 and binned in 0.2 wide bins) and a

Dear R people: I wish to switch from SPSS to R, but there is one particular type of ANOVA design that cannot be done in R. Or more likely, it can be done, but it is nowhere documented. The problem is typical for psychologists: You have a repeated measures design with different groups of subjects. Now, this can be done with the aov command, but the number of subjects in both groups must be

Dear R-help list, I am trying to do a mixed ANOVA on a 8960 x 5 dataframe. I have 3 factors for which I want to test all main effects and interactions : f1 (40 levels), f2 (7 levels), and f3 (4 levels). I also have a subject factor, subject, and a dependent variable, dv. Some more information about the factors: f2 is a between-subject factor. That is, for each level of f2 there are 8 nested

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.