similar to: ANOVA table and lmer

Hello All: I am trying to replicate the results of an example found in Alan Agresti's "Categorical Data Analysis" on pages 267-269. The example is one of a 2 x 2 cross-classification table of ordinal counts: job satisfaction and income. I am able to get Agresti's results for the independence model (G^2 = 12.03 with df = 9) assuming as he does that the data is nominal, but

Dear all, I'm analysing a split-plot experiment, where there are sometimes one or two values missing. I realized that if the data is slightly unbalanced, the effect of the subplot-treatment will also appear and be tested against the mainplot-error term. I replicated this with the Oats dataset from Yates (1935), contained in the nlme package, where Variety is on mainplot, and nitro on

When fitting a logistic regression model using weights I get the following warning > data.model.w <- glm(ABN ~ TR, family=binomial(logit), weights=WEIGHT) Warning message: non-integer #successes in a binomial glm! in: eval(expr, envir, enclos) Details follow *** I have a binary dependent variable of abnormality ABN = T, F, T, T, F, F, F... and a continous predictor TR = 1.962752

Hi, I am trying to find out how to interpret the summary output from a neg bin GLM? I have 3 significant variables and I can see whether they have a positive or negative effect, but I can't work out how to calculate the magnitude of the effect on the mean of the dependent variable. I used a log link function so I think I might have to use the antilogs of the coefficients but I have no idea

Hello, I have some trouble using step() and stepAIC() functions. I'm predicting recruitment against several factors for different plant species using a negative binomial glm. Sometimes, summary(step(model)) or summary(stepAIC(model) does not select the best model (lowest AIC) but just stops before. For some species, step() works and stepAIC don't and in others, it's the opposite.

by considering this example from barley dataset #code start dotplot(variety ~ yield | site, data = barley, scales=list(x=list(log=TRUE)), layout = c(1,6), panel = function(...) { panel.dotplot(...) #median.values <- tapply(x, y, median) # medians for each variety #panel.abline(v=median.values, col.line="red") # but this

# R for Windows will not send your bug report automatically. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs at r-project.org # ###################################################### This report is joint from Richard Heiberger <rmh at temple.edu> and Burt Holland <bholland at temple.edu>. Burt Holland is the coauthor

> get.hist.quote(instrument="INR/USD", provider="oanda", start="2005-10-20") trying URL 'http://www.oanda.com/convert/fxhistory?lang=en&date1=10%2F20%2F2005&date=11%2F01%2F2005&date_fmt=us&exch=INR&exch2=&expr=USD&expr2=&margin_fixed=0&&SUBMIT=Get+Table&format=ASCII&redirected=1' Content type

Dear R-Community! The example "oats" in MASS (2nd edition, 10.3, p.309) is calculated for aov and lme without interaction term and the results are the same. But I have problems to reproduce the example aov with interaction in MASS (10.2, p.301) with lme. Here the script: library(MASS) library(nlme) options(contrasts = c("contr.treatment", "contr.poly")) # aov: Y ~

Hi, Am I hitting some limit in match? Consider the following example: > tst<-seq(100,125,by=.2)%in%seq(0,800,by=.1) > sum(tst) [1] 76 > seq(100,125,by=.2) [1] 100.0 100.2 100.4 100.6 100.8 101.0 101.2 101.4 101.6 101.8 102.0 102.2 [13] 102.4 102.6 102.8 103.0 103.2 103.4 103.6 103.8 104.0 104.2 104.4 104.6 [25] 104.8 105.0 105.2 105.4 105.6 105.8 106.0 106.2 106.4 106.6 106.8

Hi, Am I hitting some limit in match? Consider the following example: > tst<-seq(100,125,by=.2)%in%seq(0,800,by=.1) > sum(tst) [1] 76 > seq(100,125,by=.2) [1] 100.0 100.2 100.4 100.6 100.8 101.0 101.2 101.4 101.6 101.8 102.0 102.2 [13] 102.4 102.6 102.8 103.0 103.2 103.4 103.6 103.8 104.0 104.2 104.4 104.6 [25] 104.8 105.0 105.2 105.4 105.6 105.8 106.0 106.2 106.4 106.6 106.8

Dear R users, this is a follow up of this message http://tolstoy.newcastle.edu.au/R/e6/help/09/05/13897.html I'm reproducing the core of it for convenience. > // > / data(Oats, package = "MEMSS") / > / tp1.oats <- xyplot(yield ~ nitro | Variety + Block, / > / data = Oats, / > / panel = function(x, y, subscripts, ...) { /

Dear List, I have been using R to create an xyplot using the panel function within lattice libraries. This plot is based on the data supplied in R named 'Oats'. The graph represents oat yield by nitro level with an overlay of each variety of oats for each nitro level. I have three questions regarding this graph: 1) I cannot seem to specify the type of symbol used by the plot, even though

Full_Name: Kevin Wright Version: 1.8.0 OS: Windows 95 Submission from: (NULL) (170.54.59.160) This bug also happens to me using R 1.9.0 on Windows 2000. Took me a long time to create a reproducible bug, but I think I have succeeded. I suspect my test function has a bug, but I don't see anything wrong. Plus, the bug only shows up when selecting certain filenames. Nearest I can speculate,

Hello, Are there any access functions to the various residual variables that should result from a repeated measures ANOVA ? MyAOVObject$residuals does not exist, and simply printing MyAOVObject gives a very long print of all fields in the result list, many of which I can't see what they are exactly : $error.qr$qraux, for instance. What I would like basically is to inspect those residuals

The following code produces a legend ("key") that mentions the unused levels of Block. library(MEMSS) xyplot(yield~nitro, subset=(Block=="I" | Block=="II"), data=Oats, group=Block, auto.key=T) and adding "drop.unused.levels=T" does not fix it. And in fact even the following does not solve the problem: xyplot(yield~nitro,

Dear R listers, I am trying to produce a simple (for a stata user) barplot with 4 countries on the x axis, each country observed in 2 subsequent years and 3 variables. Basically, I should have three bars for each year for each country. I am attaching the chart I made in Stata, but I am not sure you'll manage to see it! I did the following: #here I create the data-set TUSE2. The vectors mw, st

I am trying to do Tukey HSD comparisons on a repeated measures expt. I found the following example on r-help and quoted approvingly elsewhere. It is broken. Can anyone please tell me how to get it to work? I am using R 2.4.1. > require(MASS) ## for oats data set > require(nlme) ## for lme() > require(multcomp) ## for multiple comparison stuff > Aov.mod <- aov(Y ~ N + V +

When we call a lattice function such as xyplot, to what extent does the "data" designation cause the function to look inside the "data" for variables? In the examples below, the "subset" argument understands that "Variety" is a variable in the data. But the "scales" argument does not understand that "nitro" is a variable in the data.

I am using R.2.4.1 on Windows XP 5.1 (SP 2). I have the following line in my R code. Analysis=anova(lm(PM ~ x)) It works the first 60 or so times it is called but then I get the following error message. Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases In order to examine the input, I preceeded the call with the following. print(PM) print(x) This gave