search for: obrienkaiser

...inly wrong? I have the feeling that using R's "New Functions for Multivariate Analysis" (Dalgaard, 2007, R News) this could be possible, but some advice on how, would be greatly appreciated, as this does not seem to be the most straight forward way. Below is an example using the car::OBrienKaiser dataset adding an age covariate. The example is merely an adoption from ?Anova with miniml changes and includes e.g. age:phase:hour which I don't want to have. Note that I posted this question to stackoverflow two days ago (http://stackoverflow.com/q/11567446/289572) and did not receive any re...

Hi, Urgent help- I have not been using R and statistics in my research for a long time, but still remember some concept. I would like to have a sample code for Manova analysis of Split-plot experiment. Could someone please post a sample code and a short input sample as well? Thank you so much! [[alternative HTML version deleted]]

...hour <- ordered(rep(1:5, 3)) idata <- data.frame(phase, hour) mod.ok <- lm(cbind(pre.1, pre.2, pre.3, pre.4, pre.5, post.1, post.2, post.3, post.4, post.5, fup.1, fup.2, fup.3, fup.4, fup.5) ~ treatment*gender, data=OBrienKaiser) av.ok <- Anova(mod.ok, idata=idata, idesign=~phase*hour) summary(av.ok, multivariate=FALSE) If you assign the above line to a new object you will get a multivariate summary and not the univariate one. my.summary <- summary(av.ok, multivariate=FALSE) my.summary Does anyone know how to ass...

...")) hour <- ordered(rep(1:5, 3)) idata <- data.frame(phase, hour) idata mod.ok <- lm(cbind(pre.1, pre.2, pre.3, pre.4, pre.5, post.1, post.2, post.3, post.4, post.5, fup.1, fup.2, fup.3, fup.4, fup.5) ~ treatment*gender, data=OBrienKaiser) av.ok <- Anova(mod.ok, idata=idata, idesign=~phase*hour) summary(av.ok, multivariate=FALSE) ## Univariate Type II Repeated-Measures ANOVA Assuming Sphericity ## ## SS num Df Error SS den Df F Pr(>F) ## treatment 211.286 2 228...

...ted. There are different ways of representing those combinations (through names of factor levels, or coefficient vectors/matrices), and depending on the elements of that list the test is made for main effects, simple effects, interaction contrasts, etc. For instance, let me use an example with the OBrienKaiser data set (as in the help documentation for Anova() and linearHypothesis()). The calculation of the multivariate linear model and Anova is copied from those help files: > phase <- factor(rep(c("pretest", "posttest", "followup"), c(5, 5, 5)), + levels=c("pre...

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

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