similar to: help text for ave()

Dear R-developers, A student asked me today of how to specify the limits of the x-axis. I knew that he should use xlim, but I tried to encourage him to have a try himself with the various help functions. I do not judge if he used the correct search strategy or right key words, but anyway here is what he tried: he looked at ?plot. There xlim is not mentioned. He checked ?par. There you find

Dear R developers, I find the format of descriptions of the arguments in the read.table help text slightly inconsistent. For example, the logical arguments comes in seven different formats, more or less explicit about the consequences of a TRUE (or FALSE): 1. check.names logical. If TRUE then the names... 2. blank.lines.skip logical: if TRUE blank lines... 3. flush logical: if TRUE,

Dear R developers, ?help.search ...opens a tab in my browser (Firefox 3.5.6, Win XP): http://127.0.0.1:31642/library/utils/html/help.search.html When I click on the link for "?", (http://127.0.0.1:31642/library/utils/help/?) in the last line of "Details", I get an error message: "Server error: invalid response from R". Similarly, The link to "??"

Dear Sir, Many thanks for your reply. I have a query. I have a whole set of distributions which should be made normal / homoscedastic. Take for instance the warpbreaks data set. We have the following boxplots for the warpbreaks dataset: a. boxplot(breaks ~ wool) b. boxplot(breaks ~ tension) c. boxplot(breaks ~ interaction(wool,tension)) d. boxplot(breaks ~ wool @ each level of tension) e.

Dear Ashim, I?ll address your questions briefly but they?re really not appropriate for this list, which is for questions about using R, not general statistical questions. (1) The relevant distribution is within cells of the wool x tension cross-classification because it?s the deviations from the cell means that are supposed to be normally distributed with equal variance. In the warpbreaks data

Dear All, I want a transformation which will make the spread of the response at all combinations of 2 factors the same. See for example : boxplot(breaks ~ tension * wool, warpbreaks) The closest I can do is : spreadLevelPlot(breaks ~tension , warpbreaks) spreadLevelPlot(breaks ~ wool , warpbreaks) I want to do : spreadLevelPlot(breaks ~tension * wool, warpbreaks) But I get : >

Dear All, we need to do : library(car) for the spreadLevelPlot function I forgot to say that. Apologies, Ashim On Sun, Jan 7, 2018 at 10:37 AM, Ashim Kapoor <ashimkapoor at gmail.com> wrote: > Dear All, > > I want a transformation which will make the spread of the response at all > combinations > of 2 factors the same. > > See for example : > >

Hi! I'm failing to understand the value of the intercept value in a multiple linear regression with categorical values. Taking the "warpbreaks" data set as an example, when I do: > lm(breaks ~ wool, data=warpbreaks) Call: lm(formula = breaks ~ wool, data = warpbreaks) Coefficients: (Intercept) woolB 31.037 -5.778 I'm able to understand that the value of

Dear Ashim, Try spreadLevelPlot(breaks ~ interaction(tension, wool), data=warpbreaks) . I hope this helps, John ----------------------------- John Fox, Professor Emeritus McMaster University Hamilton, Ontario, Canada Web: socialsciences.mcmaster.ca/jfox/ > -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Ashim > Kapoor > Sent:

Dear R community, I'm trying to understand this behavior of TukeyHSD. My goal is to obtain defensible, labelled multiple comparisons of an interaction term. Firstly, if I plot the TukeyHSD from the model that calculates its own interactions, then the y-axis labels appear to be reflected on their median when compared to the text output of the TukeyHSD statement. The labels are integers.

Hello, I would like to do a large number of e.g. 1000 paired ttest using the by-function. But instead of using only the data within the 1000 groups, R caclulates 1000 times the ttest for the full data set(The same happens with Wilcoxon test). However, the by-function works fine with the lme function. Did I just miss something or is it really not working? If not, is there any other possibility to

I'm manipulating a large dataset and need to eliminate some observations based on specific identifiers. This isn't a problem in and of itself (using which.. or subset..) but an imprint of the deleted observations seem to remain, even though they have 0 observations. This is causing me problems later on. I'll use the dataset warpbreaks to illustrate, I apologize if this isn't in

I'm interested in restricting the pairwise comparisons of interaction effects in a multi-way factorial ANOVA, because I find comparisons of interactions between all different variables different to interpret. For example (supposing a p<0.10 cutoff just to be able to use this example): > summary(fm1 <- aov(breaks ~ wool*tension, data = warpbreaks)) Df Sum Sq Mean Sq F

Dear all, glht (from the multcomp package) needs a term and a model component in it's fitted model. In fitted models from e.g. repeated measurements ANOVAs I do not find neither model nor term. Is it possible to build together a model and term component myself, so that glht will work for repeated measurements ANOVAs? If so, how would I do that? Best regards, Michael Zehetleitner

Hi all: I have a quesion about ANOVA: Is SS(Sum of Square) of a specific factor constant with the number of factors changing? dat1 includes one factor g1,and g1's SS is called SS_g1_dat1. dat2 includes two factors g1,g2,and g1's SS is called SS_g1_dat2. My quesion is: Is SS_g1_dat1 equals to SS_g1_dat2? I have both "yes" and "no" reasons for the quesion,but

Hi, I'd like to select one row in a data frame per subset which is maximal for a particular value. I'm pretty close to the solution in the sense that I can easily select the maximal values per subset using "aggregate", but I can't really figure out how to select the rows in the original data frame that are associated with these maximal values. library(stats) # this

R Version 2.0.0 Under development (unstable) (2004-05-07) I have been wanting to use TukeyHSD for two and three way aov's, as they are especially simple for students to use correctly. I realize model simplification is usually a preferred methodology, but my disciplinary enertia and simplicity of TukeyHSD is also compelling. However, the lack of names on the comparisons for the higher order

Hi, I am seeking help with an error when running the example from R Documentation for TukeyHSD. The error occurs with any example I run, from any text book or website. thank you... > plot(TukeyHSD(fm1, "tension")). Error in plot(confint(as.glht(x)), ylim = c(0.5, n.contrasts + 0.5), ...) : error in evaluating the argument 'x' in selecting a method for function

Dear all, When I use aggregate function as: attach(warpbreaks) aggregate(warpbreaks[, 1], list(wool = wool, tension = tension), sum) The results are right but I get a warning message: "number of items to replace is not a multiple of replacement length." BTW: I use R version 2.4.1 in Ubuntu 7.04. Your kind solutions will be great appreciated. Best wishes Yours, sincerely, Xingwang

I am attempting to produce crosstabulations between two variables for subgroups defined by a third factor variable. I'm using by() and CrossTable() in package gmodels. I get the printing of the tables first and then a printing of each level of the INDICES. For example: library(gmodels) by(warpbreaks, warpbreaks$tension, function(x){CrossTable(x$wool, x$breaks > 30,