similar to: How to obtain the coefficients from a summary of aov ?

Is there an easy way of converting an aov.summary into a matrix in which the rows are the factor names and the columns are Df, Sum Sq, Mean Sq, F value and Pr. For example, convert Df Sum Sq Mean Sq F value Pr(>F) block 5 343.29 68.66 4.4467 0.015939 * N 1 189.28 189.28 12.2587 0.004372 ** P 1 8.40 8.40 0.5441 0.474904 K

I would appreciate it if someone could explain the results of the example from the aov() help file. The output given below is different from book Venables and Ripley - MASS The results In R1.5.1 (Under windows) is as follows: > N <- c(0,1,0,1,1,1,0,0,0,1,1,0,1,1,0,0,1,0,1,0,1,1,0,0) > P <- c(1,1,0,0,0,1,0,1,1,1,0,0,0,1,0,1,1,0,0,1,0,1,1,0) > K <-

Hi, I am trying to plot an interaction.plot with different color for each level of a factor. It has an erratic behavior. For example, it works for the first interaction.plot below, with the example from the ALDA book, but not with the other plots, from the NPK dataset: # from http://www.ats.ucla.edu/stat/r/examples/alda/ch2.htm tolerance <-

Hi all, Perhaps this in an inappropriate post, but I've found a bug in proj I'd like to track down a bit further before making a formal bug report. The example below shows the problem, if you change the rownames proj fails. The problem seems to be that there is a mismatch in the rownames in the qr objects constructed by aov and the rownames that proj is expecting them to have.

Hi, This might be a minor bug, or it could be that I'm just mis-using the tools (again). If you modify the example for model.tables to introduce an NA, N <- c(0,1,0,1,1,1,0,0,0,1,1,0,1,1,0,0,1,0,1,0,1,1,0,0) P <- c(1,1,0,0,0,1,0,1,1,1,0,0,0,1,0,1,1,0,0,1,0,1,1,0) K <- c(1,0,0,1,0,1,1,0,0,1,0,1,0,1,1,0,0,0,1,1,1,0,1,0) yield <-

Dear listmembers, I would like to define a class with a slot that takes either an object of class aov or NULL. I have been reading "S4 Classes in 15 pages more or less" and "Lecture: S4 classes and methods" #First I tried with list and NULL setClass(listOrNULL") setIs("list", "listOrNULL") setIs("NULL", "listOrNULL") #doesn't

I'm baffled. When I run make check after installing from source, I get a Error 2. From my understanding of how these things work, it would appear to be coming from this (as at the end of base-Ex.Rout.fail: > has.VR <- require(MASS, quietly = TRUE) Attaching package 'MASS': The following object(s) are masked from package:base : confint confint.lm nclass.FD nclass.scott

Dear statistitians / R users, I was told to analyse the effects of the four factors using lm or update for aov. The following is the result from lm. As you can see that in the last few lines enclosed coefficients. 1)Does this mean I can write a formula, like yield =0.26 + 0.03*H + 1.48*T + 0.04*L + 0.004*C 2) in the two levels design, is there any difference between I use (-1, 1) to

The following R commands were written: >help.search("factorial") >data(npk) >npk >coef(npk.aov) In the output of coef command, please explain me the interpretation of coefficients of block1 to block 6 in this 2^3 confounded factorial experiment. Thanks. [[alternative HTML version deleted]]

Hello, I noticed that model.tables fails when applied to an aov() fit if called inside a function. The problem seems to occur when as.formula is used inside a function on a string containing "<formula> + Error( x / y )" The reason I tried to use as.formula is to generate dynamic calls to aov(). Here is a minimal example illustrating the problem: ## Example test <-

Hi all, I have been trying to reproduce an analysis from Douglas Montgomery?s book on design and analysis of experiments. Table 6.10 of example 6.2 on page 246, gives a table as follows: > NPK <- expand.grid(A=mp,B=mp,C=mp,D=mp) > Rate <- c(45,71,48,65,68,60,80,65,43,100,45,104,75,86,70,96) > filtration <- cbind(NPK,Rate) > filtration A B C D Rate 1 - - - - 45 2

Dear R community, I'm currently using R to analyze functional Magnetic Resonance Imaging data. Each analysis involves running ~120,000 repeated-measures ANOVAs. I would like to know if there is any automatic way to access the F- and P-value data that are associated with each of these 120,000 ANOVAs. For example, if the summary output (for the 1st ANOVA of 120,000) shows the following value

Hi, I've done a repeated ANOVA looking as follows: model<-aov(y~a*b*c+Error(d)) Now I want to get rid of some or all of the interactions. But neither AIC nor anova work. What is the appropriate function to test my model?

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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)),

Hello!!! I'm trying to do multiple ANOVA tests with R (testing the affect off different factors on the same response). As a result I get many ANOVA tables, and I want to extract a list of the "Pr(>F)" from all the tables. Maybe someone have an idea how to do this? Thanks Imri -- View this message in context:

Hi R help, Hi R help, Which is the easiest (most elegant) way to force "aov" to treat numerical variables as categorical ? Sincerely, Andrea Bernasconi DG PROBLEM EXAMPLE I consider the latin squares example described at page 157 of the book: Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, J. Stuart Hunter, William G. Hunter. This example use

Doea anyone know how to compute components of variance analysis? For example, I have the score of pupils on a test. Each pupil belongs to a school and within each school I may have several classes? How can I estimate the variance of the pupils, schools, classes and the errror variance? Any examples? Any help will be appreciated. Jason Dr. Iasonas Lamprianou Department of Education The

Dear R users, I have the following problem: I have a table in ASCII-format, separated with commas. I can read it as long as no field contains a comma itself. If one does, read.table doesn't function even though that field is double-quoted. Ex.: File "test.csv": Name,Strasse,PLZ Jsaac,Gossauerstrassee 29,9100 Roth-Bernasconi,"20, ch. des Fauvettes",1212 adressen <-

Is there a way to prevent the re-ordering of factors by aov? I do have a three-way interaction that I do want to fit before a two-way interaction (different factors, so they are not nested), but R moves the two-way interaction to the front. I know it generally makes sense to fit the two-way interactions first, but in this case I think I know what I'm doing. + hv