similar to: Anova with Scheffe Tests

Hello, As a new user of R (less than a month) I have got my hands on several books and am pouting through the net looking for help in gaining understanding of this powerful tool. I am becoming more proficient with using basic functions to conduct basic statistics. I am now looking to learn how to write code. After a few small worthless functions I decided to try to create a function that was

Hello ALL: I am looking for multiple comparison tests for ANOVA models. Does R have any of these? Fisher least significant difference test. Tukey henestly significant difference test. Newman - Keul test. Dunnett's test Scheffe test. Thank you, ANDREW -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi, I'm designing a experiment in order to compare the growing of several clones of a tree specie. It will be a complete randomized block design. How can I decide what model of mean comparision to choose? LSD, HSD,TukeyHSD, Duncan,...? Thanks in advance

Dear all, Please help me with the R code which compute SCHEFFE TEST Thanking you in advance Kind regards Mangalani Peter Makananisa Statistical Analyst South African Revenue Service (SARS) Segmentation and Research : Data Modelling Tel: +2712 422 7357 Cell: +2782 456 4669 Fax:+2712 422 6579 Please Note: This email and its contents are subject to our email legal notice

Hello 1/ 'priors' is a table looking like: "W123" "T678" "S789" 23 42 11 12 35 9 etc 2/ WBS <- labels(priors) gives me a result of class list and length 1 looking like: "W123" "T678" "S789" I want to read W123 into X[1] as W, T687 into X[2] as T and S789 into X[3] as S using

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi. I have been using SAS for some time, and now I have discovered R. I am very happy with it, but I have not found out how to perform some of the multiple comparisons I was used to do in SAS. With the SAS/STAT, I generally used the MEANS (for comparison of arithmetic means) and the LSMEANS (for adjusted means) statements of the GLM procedure (I

Let me modify my question about user-defined covariance structures for LME models: Can somebody tell me how I can see the code for the definition of the correlation structures that come with the NLME package. Specifically I like to see the code for the functions coef, corMatrix, and intialize for any of the pre-defined correlation structures, and use this as a template to define a new correlation

Hello everyone I'm trying to use Scheffe's complete cubic model (mixture design). In the bibliographies, they indicate that the term is of the type: A * B * (A-B). But I see that trying to adjust the three cubic terms results in singularities. I know this implies not having the inverse matrix: solve (t (X)% *% X) does not exist. The bibliographies show all three cubic terms. So my

Hi, I would like to know how (if) I can extract some of the information from the summary of my nlme. at present, I get a summary looking something like this: > summary(fit.nlme) Nonlinear mixed-effects model fit by maximum likelihood Model: MLKYLD ~ W4(DIM, logA, B, C) Data: ADHIS.x0 AIC BIC logLik 265314 265401.6 -132647 Random effects: Formula: list(logA ~ 1 , B ~

Hello Instead of reading in group1.txt I want to read in groups1 for the first iteration of i, then groups2 for the second and so on. Obviously I can't use groups(i) but assume there is a way to do this. group<-read.table("C:/Data/April 2005/group1.txt",header=T) thanks in advance Meredith

I am interested in utilizing this so called "double hurdle" model in my study. We can write the model in the following way: if (z'a + u > 0 & x'b + e > 0) y = x'b + e, else y = 0 In the model, consumption y is the (left-) censored dependent variable. e and u are the normally distributed error terms. z'a is the participation equation and x'b is the

Hello, I've fitted a parametric survival model by > survreg(Surv(Week, Cens) ~ C(Treatment, srmod.contr), > data = poll.surv.wo3) where srmod.contr is the following matrix of contrasts: prep auto poll self home [1,] 1 1 1.0000000 0.0 0 [2,] -1 0 0.0000000 0.0 0 [3,] 0 -1 0.0000000 0.0 0 [4,] 0 0 -0.3333333 1.0 0 [5,] 0 0

Mangalani Peter Makananisa would like to recall the message, "Scheffe test". Please Note: This email and its contents are subject to our email legal notice which can be viewed at http://www.sars.gov.za/Email_Disclaimer.pdf [[alternative HTML version deleted]]

Dear List, are there post-hoc tests like Scheffe, LSD, etc. available after ANOVA test is performed with significant F-statistic? I have tried help.search("Scheffe"), but "No documentation found" (and I have most of packages installed). Probably there are such tests in R, and I am just searching badly... My second question is: Which test/method I should use for ANOVA-like

Dear R People: I have a few questions about multiple comparisons and contrasts for ANOVA, please. I've tried some things but with no success. Suppose I have a completely randomized design, and I want to have the contrast \mu_1 - 0.5 \mu_2 - 0.5 \mu_2 How do I set that up, please? I used the C command, and ran aov, but the results were identical to those with no contrasts. Also, is there

Dear list members, I'm running some tests looking at differences between means for various levels of a factor, using Tukey's HSD method. I would like to plot the data as boxplots or dotplots, with horizontal significance lines indicating which groups are statistically significantly different, according to Tukey HSD. Here's a nice image showing an example of such a graphical

Hi I am working on corpora of automatically recognized utterances, looking for features that predict error in the hypothesis the recognizer is proposing. I am using the glm functions to do logistic regression. I do this type of thing: * logistic.model = glm(formula = similarity ~., family = binomial, data = data) and end up with a model: > summary(logistic.model) Call:

Does anyone know of some methods already programmed up ( ie freeware : ) ) in R for the post hoc methods in anova. Particularly Scheffe's method or Tukey's? Anna

Hi, I'm trying to make sense of the options for multiple comparisons options in R. I've found the following options: pairwise.t.test, which provides standard t-tests, with options for choosing an appropriate correction for multiple comparisons TukeyHSD, which provides the usual Tukey test glht(package multcomp), which provides a variety of options >From the help list, it appears

Hello, I've got an array defined as y <- rnorm(3000), dim(y) <- c(3, 1000). I'd like to produce a 1000-element vector z that is the mean of the corresponding elements of y (like z[1,1] <- mean(y[1,1], y[2,1], y[3,1])), but being new to R, I'm not sure how to do this for all elements at once (or, at least, simply). Any help is appreciated. Thanks, Tom