similar to: how to run a mixed design ANOVA with repeated measures

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 *

In Baron and Li's "Notes on the use of R for psychology experiments and questionnaires" http://cran.r-project.org/doc/contrib/rpsych.htm they describe a balanced data set for a drug experiment: "... a test of drug treatment effect by one between-subject factor: group (two groups of 8 subjects each) and two within-subject factors: drug (2 levels) and dose (3 levels). "

Hi all, I have a strange problem and rigth now I can't figure out a solution. Trying to calculate an ANOVA with one between subject factor (group) and one within (hemisphere). My dependent variable is source localization (data). My N = 25. My data.frame looks like this: > ML.dist.stack subj group hemisphere data 1 1 tin left 0.7460840 2 2 tin left

I am new to R, therefore this might be a naive question, sorry in advance for that. I have data on 4 groups of mice (#of subjects: 8,8,8,9) where the first group is the control group and 2-4 are 3 doses of a neuro-inhibitor. For each mouse we measured the exploration time of a familiar and a new object (thus repeated measure design), and I want to test whether there are different exploration

Dear R Masters, I'm an anesthesiology resident trying to make his way through basic statistics. Recently I have been confronted with longitudinal data in a treatment vs. control analysis. My dataframe is in the form of: subj | group | baseline | time | outcome (long) or subj | group | baseline | time1 |...| time6 | (wide) The measured variable is a continuous one. The null hypothesis in

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

Hi all, after browsing the archives for hours I'm still not sure about the proper analysis for my dataset. I subjected each of about 50 critters (about 10 each in 5 distinct populations) to 4 consecutive treatments (exposure to increasing concentrations), with one measurement per treatment and individual. I, of course, want to know, if there was a treatment and / or a population effect.

I'm a journalist, wondering what questions to ask about a study that contrasted the impact on serum cholesterol of two drugs. This was a 40 dog study: 5 treatment blocks of 4 dogs each, randomized to: a control block, two blocks at different doses of drug1 and two at corresponding doses of drug2. Analysis was 2-factor repeated measures ANOVA on treatment group and sampling time. Linear

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

Hi, we are just about to evaluate R as a standard statistics package for our institute. We looked around the help - manual, the FAQ, etc. and did not find anything for the topics of random factors in ANOVA, repeated measures in ANOVA, or within subjects designs in R. Could anyone point us to any information concerning - univariate approach to repeated measures anova - multivariate

R-help, Could someone in the list write as to what is the R function to perform repeated measures ANOVA and post-hoc tests ? Thanks in advance, swami *************************************************************************** The contents of this communication are intended only for the addressee and may contain confidential and/or privileged material. If you are not the intended recipient,

Hi, I have what I believe is a repeated-measures dataset that I'm trying to analyze using lme(). This is *not* homework, but an exercise in my trying to self-teach myself repeated-measure ANOVA for other *real* datasets that I have and that are extremely similar to the following design. I'm fairly sure the dataset described below would work with lme() -- but it'd be great if anybody

All, I have a repeated measures data frame and was wondering if the covariance matrix can be calculated via some created indexing or built-in R function. Specifically, say there are 3 variables, where potassium concentration is measured 6 times on each patient. Patient number (discrete) Time (1 to 6, discrete) Potassium (continuous variable) I want the covariance/correlation matrix for the

We now have a draft of: Notes on the use of R for psychology experiments and questionnaires by Jonathan Baron and Yuelin Li at http://www.psych.upenn.edu/~baron/rpsych.htm and http://www.psych.upenn.edu/~baron/rpsych.pdf and http://www.psych.upenn.edu/~baron/rpsych.tex It is intended for students and others who are doing research in psychology. What makes it "for psychology" is that

Dear all, I have tried to use R for the repeated measures experiment design in a phonetic study, and in the resulting forms I met some problems which perturb the final interpretation of the results. I will explain the experiment design first: the same 7 subjects were answering a question about 25 linguistic stimuli; the stimuli were the same utterances which were processed in 3 different ways (3

Hi, I'm running a repeated measure ANOVA to test the effects of the within-subjects factors "congr", "isi" and their interaction, on the variable "latencies" aov(latencies ~ congr*isi + Error(subj/(congr*isi)),data=dats) "congr" has 4 levels, while "isi" has "3" levels. I would like to check for possible violations of the

Dear all, I am trying to using a mixed-design ANOVA to analyze my data. I have two between subject variables: location (2 different locations) and age group (young and old), and one within-subject variable: valence (positive, neutral, negative). I am looking at an Stevens(one between, two within) in Notes on the use of R for psychology experiments and questionnaires (P34 in this article). In

With respect to calculating the epsilon index of sphericity for ANOVA, discussed on pp. 45-47 of: http://www.psych.upenn.edu/~baron/rpsych.pdf It notes that epsilon is not required for a repeated measures design with only k=2 levels, as the minimum value of epsilon (e) is given by: e = 1/(k-1) so for k=2, we have e = 1 (ie, no correction of the F test df; see p. 46). These notes apply to a

I'm an experimental psychologist and when I run ANOVA analysis in SPSS, I normally ask for a test of non-sphericity (Box's M-test). I also ask for output of the corrections for non-sphericity, such as Greenhouse-Geisser and Huhn-Feldt. These tests and correction factors are commonly used in the journals for experimental and other psychology reports. I have been switching from SPSS to R

For those new to this list, I point out that Yuelin Li and I have drafted an introduction to R for psychology, trying to emphasize the things the psychologists usually do. It is at http://www.psych.upenn.edu/~baron/rpsych.pdf and http://www.psych.upenn.edu/~baron/rpsych.htm Because it is a draft, with frequent changes, we have not yet asked for it to be placed in the CRAN page. We welcome