similar to: Three-way interaction plot

Hello, I have a general formatting question. I have two columns of data: ColA <- c("m", "m", "m", "m") ColB<- c("d","d","d","d") And I would like to reorder them into a new column that looks like this: ColC<-

Hi All, I have a question regarding contingency tables. I would like to calculate the mean and standard deviation of a continuous variable from my own dataset based on the percentages of a contingency table I obtained from a scientific article. dataset<- data.frame(cbind(case=rep(0:1,5), x1=c(1:10), x2=c(0:9))) contingency_table<- matrix(c(100, 75, 65, 85, 90, 87), nrow=3, ncol=3) In

Dear Sirs, i just downloaded the R programm on my Macbook, but I can´t open Rcmdr, although I installed the needed Rcmdr-packages. I would be very happy, if you could help me. Telephone: +49 151 10868600 (Germany) or e-mail Yous sincerely, Selda Korkmaz sk@seldakorkmaz.com www.seldakorkmaz.com [[alternative HTML version deleted]]

Hi all, I'm trying to run a repeated measures ANOVA on some univariate ecological data that was collected over two growing seasons. I ran the test using the methodology found on this website: http://rtutorialseries.blogspot.com/2011/02/r-tutorial-series-one-way-repeated.html Upon running the actual ANOVA I got this error message: "> rmanova=anova(yearmodel, idata=yearframe,

Is there a way to use full information maximum likelihood (FIML) to estimate missing data in the sem package? For example, suppose I have a dataset with complete information on X1-X3, but missing data (MAR) on X4. Is there a way to use FIML in this case? I know lavaan and openmx allow you to do it, but I couldn't find anything in the documentation for the sem package. Thanks! -- Dustin Fife

Dear R fans, I have got a difficult sounding problem. For fitting a linear model using continuous response and then for re-fitting the model after excluding every single variable, the following functions can be used. library(MASS) model = lm(perf ~ syct + mmin + mmax + cach + chmin + chmax, data = cpus) dropterm(model, test = "F") But I am not sure whether any similar functions is

Dear John Fox, I am using Snowleopard with a Intel Core 2 Duo processor. I have installed the R console and followed your steps at: http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/installation-notes.html but every time I try "library(Rcmdr)" it loads Tcl/tk infinitely. I have tried loading "library(tcltk)" by itself and it does the same thing. I have tried with X11 running to

Hi, I am wondering if anyone knows of an easy way to fit a saturated model using the sem package on raw data? Say the data were: mtcars[, c("mpg", "hp", "wt")] The model would estimate the three means (intercepts) of c("mpg", "hp", "wt"). The variances of c("mpg", "hp", "wt"). The covariance of mpg with

Hi, Urgent help- I have not been using R and statistics in my research for a long time, but still remember some concept. I would like to have a sample code for Manova analysis of Split-plot experiment. Could someone please post a sample code and a short input sample as well? Thank you so much! [[alternative HTML version deleted]]

Dear friends, Sorry for this somewhat generically titled posting but I had a question with using contrasts in a manova context. So here is my question: Suppose I am interested in doing inference on \beta in the case of the model given by: Y = X %*% \beta + e where Y is a n x p matrix of observations, X is a n x m design matrix, \beta is m x p matrix of parameters, and e is a

I am attempting to use the R Commander Graphs Quantile-Comparison functionality on a dataset, to compare with a triangular distribution. I have the package triangle. My question is on the syntax of how to specify the parameters of the theoretical distribution in the Parameters field of the dialog box. For example, the theoretical distribution has min of 3000, max of 5000, mode of 4000. When

Dear r-devel list members, On a couple of occasions I've encountered the issue illustrated by the following examples: --------- snip ----------- > mod.1 <- lm(Employed ~ GNP.deflator + GNP + Unemployed + + Armed.Forces + Population + Year, data=longley) > mod.2 <- update(mod.1, . ~ . - Year + Year) > all.equal(mod.1, mod.2) [1] TRUE > > f <-

Hi, I have recently installed R on my mac and am trying to install R commander. When I type: install.packages("Rcmdr",dependencies=TRUE) the following message appears I have also tried installing commander via the package installer window. When I do this a large number of error messages (over 50) appear. They are mainly saying that certain dependencies are not available, or that they

Hi Folks, Please, when I ask the option reg.line at the scatterplot in package car, the OLS models includes a constant? If not how can I do it sing the following code: scatterplot(lfirms ~ lscale, data=dataset, reg.line=lm, smooth=FALSE, labels=FALSE, span=0.5, xlab="Relative Plant Fixed Cost", ylab="Relative Number of Firms", pch=c(18),

Hi I have data from 12 subjects. The measurement is log(expression) of a particular gene and can be assumed to be normally distributed. The 12 subjects are divided into the following groups: Infected, Vaccinated, Lesions - 3 measurements Infected, Vaccintaed, No Lesions - 2 measurements Infected, Not Vaccinated, Lesions - 4 measurements Uninfected, Not Vaccinated, No Lesions - 3 measurements

hi, i did a 2^4 factorial experiment, and i got the following result: Effect t p (computer) p -484.52494328125 -5.64590926071629 <0.0001 d -450.67095078125 -5.25142684568607 <0.0001 pd 438.80508046875 5.11316022388923 0.0001 t 351.87216640625 4.1001776078805 0.0008 pt -341.05023984375 -3.97407550262202 0.0011 dt -311.27784109375

Hi, All! To calculate Levene's Test for Homogeneity of Variance I use R Commander, and this is the output: > levene.test(Dataset$age, Dataset$sex) Levene's Test for Homogeneity of Variance Df F value Pr(>F) group 1 0.8739 0.3567 33 I am not sure what means "Pr(>F)"? Can anyone explain/translate this? Regards, Iurie Malai Department of Psychology and

Hello, I have a MANOVA model and I want to test the following hypothesis: LBM = 0 where B is the parameter estimates. Is there any function to do this in R? Cheers, Philippe -- Philippe Hup? Institut Curie, CNRS UMR 144, INSERM U900 26 rue d'Ulm 75005 Paris - France Email : Philippe.Hupe at curie.fr T?l : +33 (0)1 56 24 69 91 Fax: +33 (0)1 56 24 69 11 website :

Hi, I am wondering if there is a similar effects package for mixed models, just like what effects package does for linear, generalized linear models? Specifically I am looking for a way to calculate the SAS-co-called least squared means (LS means) in mixed models (I understand there is a substantial debate on whether such adjusted means should be computed in the first place). Thank you, John

Using ordered probit model, I get errors from dwt and bptest. dwt: Error in durbinWatsonTest.default(...) : requires vector of residuals bptest: Error in storage.mode(y) <- "double" : invalid to change the storage mode of a factor I imagine I have to restate as an individual probit model for each category, but is there an easier way? thanks, bp [[alternative HTML version