similar to: Help writing a Scheffe Contrast function for R

Hi R-people, I am wanting to run Factorial ANOVA followed by Scheffe tests on some spatial subjective data. I'm comparing X-Y independent coordinates against x-y dependent coordinates. There are only four independent spatial coordinates that form a square. I am wondering whether I am doing the right thing, because there doesn't seem to be a simple way of doing this. I have attempted to

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

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]]

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

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

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

Hello, I am interested in parametric multi comparison tests such as Dunnett, Duncan, Tukey, Newman-Keuls, Bonferonni, Scheffe, and non-parametric tests such as Kruskal-Wallis, and Mann-Whitney U. Are there packages that include most of these tests in each category? Many packages exist for an individual test but their outputs vary in great detail (test statistics, p-values, etc.)

All, I have been reading Dr. Harrell's excellent "Regression Modeling Strategies" book and trying out the exercises. I understand that contrast( ) is used to obtain contrasts between two variables for given levels of other nuisance variables; is there a way to use contrast( ) to obtain, for example, Scheffe confidence intervals / hypothesis tests for many post hoc contrasts at

Greetings all, I've done some ANOVAs and have found significant effects across my groups, so now I have to do some post-hoc tests to ascertain which of the groups is driving the significant effect. Usually one would do something like a Newman-Keuls or Scheffe test to get at this but based on googling and browsing through the r-help archives R doesn't support these and they seem to be

Hello everybody, shame on me if I have overlooked something (CRAN, StatLib), but I think I've searched carefully. Maybe it's just too obvious to see for me (happens frequently). Is a function available that extracts multiple comparison of means from objects produced by "aov()" ? Sorry if the term is not correct, I translated from german word by word ("Multiple

This is maybe not directly an R problem but I have used R to try to solve it so I think somebody may be able to help. I have a mixture model with three components and a quadratic Scheffe polynomial p1x1+p2x2+p3x3+p12x1x2+p13x1x3+p23x2x3 fitted to the response. Now I'd like to compute the mixture corresponding the maximum response. Model for Y1 has the parameters p1=124.02 p2=60.973 p3=41.479

To my understanding, a confidence interval typically covers a single valued parameter. In contrast, a confidence band covers an entire line with a band. In regression, it is quite common to construct confidence and prediction bands. I have found that many people are connecting individual confidence/prediction interval values produced with predict(object,sd.fit=T,type="conf/pred") and

Hi, we are just about to evaluate R as a standard statistics package for our institute. We looked around the help - manual, the FAQ, etc. and did not find anything for the topics of random factors in ANOVA, repeated measures in ANOVA, or within subjects designs in R. Could anyone point us to any information concerning - univariate approach to repeated measures anova - multivariate

Hello, I send the message again with the data file as txt because it seems not to be accepted as csv in the R-help list. Data comes from a multiyear field experiment in which 4 levels of a treatment (2, 3, 4, 6) are compared to see the effect on yield. It is a randomized complete block design. The SAS code follows: options ls=95; data uno; infile 'data.txt'

Evidently my RSeek capabilities have once again failed me...By any chance is Scheffe's method (http://www.itl.nist.gov/div898/handbook/prc/section4/prc472.htm) implemented independently in any R base packages? If not, is it implemented independently in any of the add-on packages? Thanks again for any insights.

We had problems with our mail server. I have no idea whether this message has reached the list or whether there were any replies. So I retry ... ------------------------ Date: Wed, 5 May 1999 16:42:55 +0200 (CEST) From: "Uli Flenker; Raum 704" <uli at pcinternet.biochem.dshs-koeln.de> To: R-Mailing-List <r-help at stat.math.ethz.ch> Subject: ANOVA "ex post"

Dear all, I am doing a one way between subjects anova in an unbalanced data set. Suppose we have "a" levels of the one factor. I want to merge the not so significantly different levels into the same cluster. Can I do a Tukey Kramer HSD and then use the following algorithm: For i in 2 : "a" For j in 1 : i-1 if mean of level i is not significantly different

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

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

I'm having speed problems with the SCSI card we're using to do tape backup. It seems to be functioning in 16 bit mode and the current thinking is that perhaps it's using a legacy driver instead of the correct one. The Adaptec site has a 'driver' for RHEL5 which I've downloaded and tried to install but it seems to have a problem installing on a CentOS-5 system. [root at