similar to: Testing for parallel slopes

Hi, How would one go about determining if the slope terms from an analysis of covariance model are different from eachother? Based on the example from MASS: library(MASS) # parallel slope model l.para <- lm(Temp ~ Gas + Insul, data=whiteside) # multiple slope model l.mult <- lm(Temp ~ Insul/Gas -1, data=whiteside) # compare nested models: anova(l.para, l.mult) Analysis of Variance

Dear List-members, Hopefully someone will help through my confusion: In order to get the same coefficients as we get from the following ## require (MASS) summary ( lm(Gas ~ Insul/Temp - 1, data = whiteside) ) ...................... we need to do the following (if we use model.matrix to specify the model) ## summary ( lm(Gas ~ model.matrix(~ Insul/Temp - 1) - 1, data = whiteside) )

I fit the model fit<-lm(thresh~cond*Ne) where thresh is the reponse cond is a factor with levels a, b, and c Ne is a continuous indep var I think of this full model as having three lines: thresh as a function of Ne for each condition. Thus we have slopea, slopeb, slopec, inta, intb, intc. lm output my params ------------------------- (Intercept) inta condb intb - inta condc

A pragmatic solution could be to create a simple linear regression example with variables in the global environment and then another example with a data.frame. The latter might be somewhat more complex, e.g., with several regressors and/or mixed categorical and numeric covariates to illustrate how regression and analysis of (co-)variance can be combined. I like to use MASS's whiteside

On 6/23/05, RenE J.V. Bertin <rjvbertin at gmail.com> wrote: > Hello, > > I was just having a look at the aov function source code, and see that when the model used does not have an Error term, Helmert contrasts are imposed: > > if (is.null(indError)) { > ... > } > else { > opcons <- options("contrasts") >

Hello everyone, Can anyone tell me how do I restore data in a data.frame provided by base R libraries (MASS) ? I uninstalled R then installed it again and I still see the new changes I made!!!??? (eg. whiteside$Temp=1 ==> 1 overwrote all the rows, I want the old values :( !! Please HELP! -- View this message in context:

I'm wondering which textbook discussed the various contrast matrices mentioned in the help page of 'contr.helmert'. Could somebody let me know? BTW, in R version 2.9.1, there is a typo on the help page of 'contr.helmert' ('cont.helmert' should be 'contr.helmert').

R-helpers; I tried to get a superscripted 3 in the following xyplot example but failed: >data(whiteside) >xyplot(Gas ~ Temp | Insul, whiteside, panel = function(x, y, ...) { panel.xyplot(x, y, ...) panel.lmline(x, y, ...) }, xlab = "Average external temperature (deg. C)", ylab = paste(paste("Gas consumption (1000", expression(ft^3),")"), aspect

On Sat, 15 Dec 2018, frederik at ofb.net wrote: > I agree with Steve and Achim that we should keep some examples with no > data frame. That's Objectively Simpler, whether or not it leads to > clutter in the wrong hands. As Steve points out, we have attach() > which is an excellent language feature - not to mention with(). Just for the record: Personally, I wouldn't recommend

I think this site is always failing. It has an embedded video. http://www.sportsnet.ca/basketball/nba/free-association-podcast-much-toronto-raptors-fear-miami-heats-dwayne-wade-hassan-whiteside-joe-johnson/ I tried looking at the output of strace firefox > fferrors.txt 2>&1 grep ENOENT fferrors.txt hope that helps Note: I also have ffmpeg with nux's repo installed On Mon, May

Page 140 of MASS uses the function xyplot. But I don't find it in R. Is there a package that I should load to use xyplot. Or there is a function with a different name in R that does the same thing as xyplot in S. xyplot(Gas ~ Temp | Insul, whiteside, panel = function(x, y, ...) { panel.xyplot(x, y, ...) panel.lmline(x, y, ...) }, xlab = "Average external temperature (deg. C)", ylab

I frequently get data sets with cryptically-named variables. The datasets are more useful to me with informative variable names. I know that I can rename variables using the following command: dimname(dataset[[2]][index.of.variable.to.be.renamed]<-new.variable.name If I want to do this inside a function (say something I call RenameCol) what is the best way to communicate the

R folks, As an R novice, I struggle with the mystery of subsetting. Textbook and online examples of this seem quite straightforward yet I cannot get my mind around it. For practice, I'm using the code in MASS Ch. 6, "whiteside data" to analyze a different data set with similar variables and structure. Here is my data frame: ###subset one of three cases for the variable

Hi all, I have currently been using the book Modern Applied Statistics with S from Venables and Ripley. At chapter 6 on Linear Statistical models I wanted to produce the plot as shown by "Figure 6.1" using Whiteside's data. xyplot command seems not to work on my version of "R"(version 1.7.0) running on different environments (Win XP, Win 98 and Win 2000). I then used the

I'm trying to adapt some S-Plus scripts to run in R (1.2.2, Windows). In one of these scripts, I've bootstrapped the prediction success rate under the discriminant function (lda). The bootstrap() functions are proprietary to S-Plus and there aren't exact equivalents in R. The closest is Canty's library boot based on the Davidson and Hinkley book. Unfortunately, I

Hi, I found that using different contrasts (e.g. contr.helmert vs. contr.treatment) will generate different fitted probabilities from multinomial logistic regression using multinom(); while the fitted probabilities from binary logistic regression seem to be the same. Why is that? and for multinomial logisitc regression, what contrast should be used? I guess it's helmert? here is an example

Hi, perhaps this is a stupid question, but i need some help about Helmert contrasts in the Cox model. I have a survival data frame with an unordered factor `group' with levels 0 ... 5. Calculating the Cox model with Helmert contrasts, i expected that the first coefficient would be the same as if i had used treatment contrasts, but this is not true. I this a error in reasoning, or is it

Hi Folks, I've encountered something I hadn't been consciously aware of previously, and I'm wondering what the explanation might be. In (on another list) using R to demonstrate the difference between different contrasts in 'lm' I set up an example where Y is sampled from three different normal distributions according to the levels ("A","B","C")

Dear R users, When fitting a lme() object (from the nlme library), is it possible to test interactions *before* main effects? As I understand, R conventionally re-orders all terms such that highest-order interactions come last - but I??d like to know if it??s possible (and sensible) to change this ordering of terms. I??ve tried the terms() command (from aov) but I don??t know if something

I am using RW 1.2.3. on an IBM PC 300GL. Using the data bp.dat which accompanies Helen Brown and Robin Prescott 1999 Applied Mixed Models in Medicine. Statistics in Practice. John Wiley & Sons, Inc., New York, NY, USA which is also found at www.med.ed.ac.uk/phs/mixed. The data file was opened and initialized with > dat <- read.table("bp.dat") >