similar to: Anova's in R

Full_Name: Martin Frith Version: R-2.0.0 OS: linux-gnu Submission from: (NULL) (134.160.83.73) I have large vectors containing 100,000 to 20,000,000 numbers. However, they only contain a few hundred *distinct* numbers (e.g. positive integers < 200). When I do ecdf(v), it either runs out of memory, or it succeeds, but when I plot the ecdf with postscript, the output is unnecessarily bloated

Hi, I have a situation I''m hoping someone out there may be able to shed some light on. I have a Rails app (2.1.0 on Ruby 1.8.7) with a wizard-based sign up process, that has recently been changed from storing incremental data in the database to having a medium sized object graph living in the user session until the user completes the entire sign up process (this is a business

Hi all, I'm trying to get postfix and dovecot working nicely together to process and store mail for both local (system) on one domain and virtual users and a few different domains. I've got postfix up and running quite nicely, but am having a few problems with Dovecot. Every time postfix tried to delivery a message to a virtual user using dovecot I get an error like the following in

Hi, My name is Dan Ott and I recently learned R mainly for the purposing of running ANOVA's and linear regression. I just started using a data set where I want to run a repeated measures anova as well as a split-plot anova. My question is: What is the syntax for repeated measures and split-plot anova's? I did a little searching online and it appears that aov might be used for a

Hi, I'm running Samba as a glorified NAS at the moment - to begin with, I have an ext3 storage partition, /storage. In this is a directory, /storage/Personal, which has its own Samba share (also Personal). At this point, dos attributes using filesystem xattrs work beautifully. The problem comes when I start to fiddle further... I have a Novell NetWare filesystem (ncpmount) mounted at

I have to perform ANOVA's on many different data organized in a dataframe. I can run an ANOVA for each sample, but I've got hundreds of data and I would like to avoid manually carrying out each test. in addition, I would like to have the results organized in a simple way, for example in a table, wich could be easy to export. thank you for assistance simone

I want to write a function to take an argument as the response variable of a linear model, e.g. to do anova's across a list of variables, something like the following (except, of course, this doesn't work): function(x) { anova(lm(x ~ my.factor,data=my.data)) } The x in lm() above is getting evaluated at the wrong level. How can I make this work? -- Russell Senior ``The two

Hi, Newbie here, just joined the list. I discovered something interesting when performing a mixed between and within (repeated measure) ANOVA in R. The error terms (SS actually I guess) are inflated by the number of factors of the within measure. This just seems wrong. I think I'm doing it right e. g. subj grp test x 1 1 1 ... 1 1 1 1 1 2 1 1 2 2 2 1 2 2 1 2 2 2 2 2 2 So, the anova

I'd like to conduct one-way ANOVA's on multiple IV's. Is there a function for "aov (y~"all of my IV's")? Thank you! -- View this message in context: http://r.789695.n4.nabble.com/ANOVA-with-many-IV-s-tp3583788p3583788.html Sent from the R help mailing list archive at Nabble.com.

Hi all This is probably a simple problem but somehow I am having much trouble with finding a solution, so I seek your help! I have a data-set with continuous response variables. The explanatory variably is 4xpH treatments (so 8.08, 7.94, 7.81 and 7.71) so also continuous and not technically factorial. However I have decided to do Anova's (as well as regression) to explore the effect of

Using a "by() statement, I am preparing ANOVA's for multiple experiments, and using simint() to generate confidence intervals. This works fine. simint.by.fit <- by(analytes.dfr, list(Assay = analytes.dfr$analyte ), function(data) (simint(value ~ tx, data = data,type='Tukey' ) ) ) I can separately prepare plots of the confidence intervals, and I can prepare separate plots

I am running lrm() with a single factor. I then run anova() on the fitted model to obtain a p-value associated with having that factor in the model. I am noticing that the "Model L.R." in the lrm results is almost the same as the "Chi-Square" in the anova results, but not quite; the latter value is always slightly smaller. anova() calculates the p-value based on

Hi I try to implement a simple 2-factorial repeated-measure anova in the lme framework and would be grateful for a short feedback -my dependent var is a reaction-time (rt), -as dependent var I have -the age-group (0/1) the subject belongs to (so this is a between-subject factor), and -two WITHIN experimental conditions, one (angle) having 5, the other 3 (hands) factor-levels;

Hey Folks: New to R and learning as I go, but really, I know just enough to get myself into trouble. I've waded through everything up till now, and don't see anything in the search that is directly helpful for the POS that I've created. The GOAL: All I want in the world is a program that performs 1-way ANOVA's on every column in a data set (taking the first column as the

Hi, I need to create a data frame containing the results of a number of ANOVA's but I'm having some trouble setting it up (some being enough for me to spend 3 days trying with no progress and be left staring in to the abyss which some people call a weekend, and what I will call 2 quiet days in the office...) The response variable is *V*. I need to do an ANOVA for each *G*. The fixed

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 I am comparing four different linear mixed effect models, derived from updating the original one. To compare these, I want to use anova(). I therefore do the following (not reproducible - just to illustration purpose!): dat <- loadSPECIES(SPECIES) subs <- expression(dead==FALSE & recTreat==FALSE) feff <- noBefore~pHarv*year # fixed effect in the model reff <-

Hi, As part of my dissertation, I'm going to be doing an Anova, comparing the "dead zone" diameters on plates of microbial growth with little paper disks "loaded" with antimicrobial, a clear zone appears where death occurs, the size depending on the strength and succeptibility. So it's basically 4 different treatments, and I'm comparing the diameters (in mm) of

On 25/02/2011 21:22, Ben Ward wrote: > > -------- Original Message -------- > Subject: Re: [R] ANOVA and Pseudoreplication in R > Date: Fri, 25 Feb 2011 12:10:14 -0800 > From: Bert Gunter<gunter.berton at gene.com> > To: Ben Ward<benjamin.ward at bathspa.org> > CC: r-help<r-help at r-project.org> > > > > I can hopefully save bandwidth here by

Hi there, Can anyone please tell me if it is possible to limit parameters in nlrq() to 'upper' and 'lower' bounds as per nls()? If so how?? Many thanks in advance