search for: multifactori

dear list, i am using a multifactorial design with two treatments (factor A: drugs, three levels; factor B: theraphy, two levels) and a time factor (three levels, different timepoint). hypothetically, i measured the same subjects for all treatements and timepoints, so its a repeated measurement design. now i ran an anova in R and also...

Hi, If I have two sets of directional data (in radians) and want to compare them with a multifactorial anova. Is it even legitimate to compare circular data with an anova? The books I've picked up from the library don't really say, but it looks unlikely. If it is allowable, is my having stored the data as circular (X = as.circular(A)) something the aov() function will take into account,...

...head and analyse it further. When I use SSPos11 as te only fixed effect, it does it is not significant in either anova nor t-test, and a boxplot of the factor shows that the levels are all quite similar (similar variance and mean). Might the effect I observe be linked to an unbalance design in the multifactorial model? thanks a lot for your help, +kind regards, Arne > anova(fit) numDF denDF F-value p-value (Intercept) 1 540 323.4442 <.0001 SSPos1 3 540 15.1206 <.0001 ... SSPos11 3 540 1.1902 0.3128 ... > summary(fit) Linear mixed-effect...

...use these as input into the sem package for structural > equation models. If anyone thinks that is misguided I would be intersted to > here. > > Michael Dewey > m.dewey at iop.kcl.ac.uk As you might know, there are various ways you can fit what in the genetic literature is called a multifactorial threshold model (MFT ie tetra/polychoric correlation model). The simplest is to treat them as Pearson correlations and use conventional SEM methods, which often works well (esp for large dimensional problems); the AWLS method of Browne as implemented for example in LISREL (needs large N); or ful...

I'm writing a script which puts together a bunch of graphs and outputs them to a graphics device. One of the things I want to add is ANOVA summaries but I'm having trouble with formatting them for graphics. I do this: anova_summary <- summary(aov(concentration~inhibition*genotype, data =drug_data)) print(anova_summary) The printout to the R console is in the format I want but if I

Dear R experts, For quite some time I have been trying to solve a mistery of reading a seemingly trouble-free text file. The data is temperature reconstruction arranged as a huge grid, preceded by seven "header lines" (which you see better if file is opened in Firefox or Chrome). This is the data (gridded temperature reconstruction)

Si puedo dar mi opinión es que no uséis rcomander. Al final el alumno cree que usa R pero no lo usa!!! Depende del tiempo pero si es para psicología yo usaría excell o spss. Rcomander les va a liar mas de lo debido y deja el ordenador inutilizable... Soy profe de estadistic pero aparte estoy en segundo de psicologia y la estadistica que se da es muy muy basica como para usar R. Salutis. Renaud