similar to: repeated measures with a group factor

Hi, sorry if this is explained somewhere but I didn't find anything. How can I use "Anova" from the car package to test a modell without between subject's factors? Suppose I have the following data mat.1 mat.2 mat.3 di ex 1 85 85 88 1 1 2 90 92 93 1 1 3 97 97 94 1 1 4 80 82 83 1 1 5 91 92 91 1 1 6 83 83

Data set up as one observation/subject looks like (with a total of 10 subjects) Two treatments: shoe type with 3 categories and region with 8 categories ==> 24 "treatment" columns Subject PHallux PMidToes PLatToe PMTH1 PMidMTH PLatMTH PMidfoot PRearfoot LHallux LMidToes LLatToe LMTH1 LMidMTH LLatMTH LMidfoot LRearfoot DHallux DMidToes DLatToe DMTH1 DMidMTH DLatMTH

Dear list member, I deperately need an help in performing a MANOVA in R, but I encountered some problems both in the design and in the synthax with R. I conducted a listening experiment in which 16 participants had to rate the audio stimuli along 5 scales representing an emotion (sad, tender, neutral, happy and aggressive). Each audio stimulus was synthesized in order to represent a

Hi all, I'm trying to run a repeated measures ANOVA on some univariate ecological data that was collected over two growing seasons. I ran the test using the methodology found on this website: http://rtutorialseries.blogspot.com/2011/02/r-tutorial-series-one-way-repeated.html Upon running the actual ANOVA I got this error message: "> rmanova=anova(yearmodel, idata=yearframe,

Hello all, I am getting the following error: Error in linear.hypothesis.mlm(mod, hyp.matrix.1, SSPE = SSPE, V = V, : The error SSP matrix is apparently of deficient rank = 7 < 11 After running: mod.ok <- lm(as.matrix(dat[,-1]) ~ DC, data=dat) (av.ok <- Anova(mod.ok, idata=idata, idesign=~week)) Although if I jitter the data in "dat", the function seems to work. What

Env: R 2.8.1, Win Xp, Eclipse/StatET In a .Rd file, I have an example containing the lines: # calculate Y M, using polynomial contrasts trends <- as.matrix(VocabGrowth) %*% poly(8:11, degree=3) colnames(trends)<- c("Linear", "Quad", "Cubic") [At the risk of a long message, I'll append the complete .Rd file at the end of this message, in case this was

To whom it may concern I made some analysis with R using the command Anova. However, I found some problmes with the output obtained by selecting type II o type III sum of squares. Briefly, I have to do a 2x3 mixed model anova, wherein the first factor is a between factor and the second factor is a within factor. I use the command Anova in the list below, because I want to obtain also the sum

For some time I have been looking for a convenient way of performing post-hoc analysis to Repeated Measures ANOVA, that would be acceptable if sphericity is violated (i.e. leaving aside post-hoc to lme models). The best solution I found was John Fox's proposal to similar requests in R-help: http://tolstoy.newcastle.edu.au/R/e2/help/07/09/26518.html

Hi, I have a experiment with block, plots, sub-plots, and sub-sub-plots with repeated measures and 3 factors (factorial design) when we have been observed diameter (mm), high (cm) and leaves number (count). However, we don't have one treatment in one factor, so, my design is unbalanced. On a previous message here, a friend tell me that "It appears to me that your design is a split-split

Dear R-Users, I'm trying to set up a repeated measures anova with two within subjects factors. I tried it by 3 different anova functions: aov, Anova (from car package) and lme (from nlme package). I managed to get the same results with aov and Anova, but the results that I get from lme are slightly different and I don't figure out why. I guess I did not set up the error structure

Dear helpers, I have a 2x2 mixed design with two "groups" (between-subjects) and two presentation-types (within-subjects). The difference between groups is in the order of manipulations: group.CD having first a block of present.type.C and then a block of present.type.D, each block containing 31 trials. group.DC having first a block of present.type.D and then a block of present.type.C,

I have design with two repeated-measures factor, and no grouping factor. I can analyze the dataset successfully in other software, including my legacy DOS version BMDP, and R's 'aov' function. I would like to use 'Anova' in 'car' in order to obtain the sphericity tests and the H-F corrected p-values. I do not believe the data are truly deficient in rank. I

Dear list, I would like to run an ANCOVA using car::Anova with repeated measures factors, but I can't figure out how to do it. My (between-subjects) covariate always interacts with my within-subject factors. As far as I understand ANCOVA, covariates usually do not interact with the effects of interest but are simply additive (or am I wrong here?). More specifically, I can add a covariate as

Dear R users, I use the excelent Anova function of the library car because the easy way to get sphericity correction. Unless I use the scan function. I have not been able to access the values ​​of sum squares and degrees of freedom for each effect in the univariate summary table. Example of the car library for Anova function: library(car) phase <- factor(rep(c("pretest",

Hello everyone, I've conducted a Type III repeated-measures ANOVA using Anova() from the car package, based on the suggestions at http://blog.gribblelab.org/2009/03/09/repeated-measures-anova-using-r/(option 3) and http://languagescience.umd.edu/wiki/EEG#ERP_ANOVA_in_R. My ANOVA has two factors: Condition (3 levels) and Region (6 levels) and their interaction. Below is code to run the Anova

I would like to perform multiple comparisons or post-hoc testing on the independent variable in an Anova.mlm object generated by the Anova function of the car package. I have defined a multivariate linear model and subsequently performed a repeated measures ANOVA as per the instructions in section #3 of the following comprehensive tutorial on the subject from the Gribble lab at UWO:

Dear list member, My question is related to input file format to an Anova from car package. Here is an example of what I did: My file format is like this (and I dislike the idea that I will need to recode it): Hormone day Block Treatment Plant Diameter High N.Leaves SH 23 1 1 1 3.19 25.3 2 SH 23 1 1 2 3.42 5.5 1 SH 23 1 2 1 2.19 5.2 2 SH 23 1 2 2 2.17 7.6 2 CH 23 1 1 1 3.64 6.5 2 CH 23 1 1 2

Hello dear R members. I have been learning the Anova syntax in order to perform an SS type III Anova with repeated measures designs (thank you Prof. John Fox!) And another question came up: where/what are the (between/within) residuals for my model? ############ Play code: phase <- factor(rep(c("pretest", "posttest", "followup"), c(5, 5, 5)),

Dear R-users, I have 3 plant populations (fixed). Within each population there is the same number of “families” (random) – the seed progeny of the same plant. These families were exposed to 2 treatments (fixed) and their response was measured (mean values for 25 seedlings per family per treatment are presented in data table). I would like to know if there is a significant difference in the

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