similar to: computing a p-value for a one-way ANOVA given only means and std dev of 5 factor levels

Thanks to Rolph Turner and Jason Turner ... I guess I was too excited about getting back on the list after an absense of several years ... I'll be a little more thoughtful about the problem before posting next time, and a little less trigger-happy with the "Send" e-mail button. Never-the-less, much appreciated. - Mohamed -----Original Message----- From: Rolf Turner

It's cool, it's exciting, and much thanks to Duncan. He announced RJava yesterday (or this morning?) on the R-devel list, and it's really worth it. http://www.omegahat.org/RSJava for more details. But it does mean that we can run Orca code directly within R, (without Thomas' socket connections) (and also means that we really need a "stop" button, since killing

Hi, I am creating a new backend for a custom microcontroller. In order to create the backend I am modifying from Mips backend. My architecture has a store instruction with direct address mode. It accepts two arguments: source register and address (immediate). This instruction is not available in Mips, but it is in Hexagon, so I copied from Hexagon the following, adapting it to my registers: -

Greetings: I'm still working on functions to make it easier for students to interpret regression predictions. I am working out a scheme to more easily create "newdata" objects (for use in predict functions). This has been done before in packages like Zelig, Effects, rms, and others. Nothing is "exactly right," though. Stata users keep flashing their "predicted

Hello, I'm new in R. I'm meteorological modeller and i will calculate some statistics for my model results. These statistis are the follow: ANB: Average Normalized Absolute BIAS MNB: Mean Normalized BIAS MNE: Mean Normalised Error STDE: Standard Deviation of Error FB: Fractional BIAS MG: Geometric Mean BIAS VG: Geometric Variance SKVAR: Skill Variance RMSE: Root Mean Square Error NMSE:

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Dear all, In the process of investigating a performance difference between Clang & GCC when both compile the same non-toolchain program while using the "same"* compiler flags, I have found something that may be worth changing in Clang, developed a patch, and confirmed that the patch has its intended effect. *: "same" in quotes b/c the essence of the problem is that the

Dear all, I calculate the test statistic for the KS test outside R, and wish to use R only to calculate the corresponding p-value. Is there a way for doing this? (as far as I see, ks.test() requires raw data as input). Alternatively, is there a way to provide the ks.test() the two CDFs (two samples test) rather than the (x, y) data vectors? Thanks in advance, Rani

Hi, I noticed that with the GCC trunk (4.3.0), the semantics of "extern inline" have reversed. The net result is that R will build without the usual-stdc=gnu99 but it won't with it. Many multiple definitions result otherwise. Marcus

Hello I have run an anova analysis for the fallowing model: H_obs=mu+REGION+MANAGEMENT + e When I run it in ASRelm I get the p-value for mu, and, of course also for the two dependent variables (REGION and MANAGEMENT) When I run it in R, I do not get the pvalue for mu. Can some one help me to understand why? and if it is possible to estimate the pvalue for mu in anova() in R? I attach the

Hi I have done ANOVA on a dataset (See Below) but am having problems retreiving the p-value. I am assuming that Pr(>F) is the p-value but cannot get this value or in fact any other value (e.g. DF) from the summary.Any suggestions?? I have tried sum<-summary(zzz.aov) > sum$Pr(>F) Error: unexpected '>' in "sum$Pr(>" > sum$"Pr(>F)" NULL >

Hi all, I'm tryint to turn my ANOVA result from anova(model) in to p values. The default output is: term ; Df ; Deviance ; resid Df; Resid. Dev Is there a way to add p values to this output so the significance of the terms can be easily determined? Thanks in advance. Richie [[alternative HTML version deleted]]

Hello, everybody, There is the first time for me to post a question, because I really cannot find answer from books, websites or my colleagues. Thank you in advance for your help! I am running likelihood ratio test to find if the simpler model is not significant from more complicated model. However, when I run LRT to compare them, the test did not return F value and p-value for me. What's the

hello all, Quick question, how do I get the p value out of the anova? Thanks, Paul > pb<-aov(as.numeric(diff[5,16:33]) ~ grF) > summary(pb) Df Sum Sq Mean Sq F value Pr(>F) grF 3 2.7860e+10 9.2867e+09 4.2236 0.02534 * Residuals 14 3.0783e+10 2.1988e+09 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 '

Hello dear R help members. I am trying to understand the anova.rq, and I am finding something which I can not explain (is it a bug?!): The example is for when we have 3 nested models. I run the anova once on the two models, and again on the three models. I expect that the p.value for the comparison of model 1 and model 2 would remain the same, whether or not I add a third model to be compared

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

Hello, I am using R to analyze a large multilevel data set, using lmer() to model my data, and using anova() to compare the fit of various models. When I run two models, the output of each model is generated correctly as far as I can tell (e.g. summary(f1) and summary(f2) for the multilevel model output look perfectly reasonable), and in this case (see below) predictor.1 explains vastly more

Dear useRs, I am using mgcv version 1.7-16. When I create a model with a few non-linear terms and a random intercept for (in my case) country using s(Country,bs="re"), the representative line in my model (i.e. approximate significance of smooth terms) for the random intercept reads: edf Ref.df F p-value s(Country) 36.127 58.551 0.644

Is there a way of extracting mean distance or dissimilarity for a given strata from a 'dist' or 'dissimilarity' object, e.g. extract mean distances for each species in Anderson's iris data? data(iris) iris.dist<-dist(iris[,1:4]) then what? Mikkel Grum, PhD Genetic Diversity Scientist International Plant Genetic Resources Institute (IPGRI) Sub-Saharan Africa Group ***

K-means recluster data with given cluster centers Dear R user, I have several large data sets. Over time additional new data sets will be created. I want to cluster all the data in a similar/ identical way with the k-means algorithm. With the first data set I will find my cluster centers and save the cluster centers to a file [1]. This first data set is huge, it is guarantied that cluster