similar to: lattice: drawing strips for single-panel plots

Suppose you have the following code: ########## Start code########## data(Chem97, package="mlmRev") densityplot(~gcsescore | factor(score), groups=gender, data=Chem97, auto.key=TRUE, plot.points=FALSE, ref=TRUE, panel=function(x,...){ panel.densityplot(x,...) median.values <- median(x)

Dear list, I've written a small utility function to add arbitrary legend(s) to a lattice graph (or a combination of them), much like the legend function of base graphics. I though perhaps it could be useful to someone else, or improved by suggestions. I understand this goes against the lattice paradigm somewhat, in that you short-cut the link between group variables and the

Hello, running a mixed model in the package LME4, lmer() Panel data, have about 322 time periods and 50 states, total data set is approx 15K records and about 20 explanatory variables. Not a very large data set. We run random intercepts as well as random coefficients for about 10 of the variables, the rest come in as fixed effects. We are running into a wall of time to execute these models.

Dear list users, I modeled the probability of occurrence of one species: "Cyperus dilatatus". I modeled the species using three different approaches: c("random","target","index") What I want to achieve is to make a plot of all prediction maps in a row with to conditional variables, that is, with the species and the approach I prepared a data.frame to try

Dear All, I'm trying to model heteroscedasticity using a multilevel model. To do so, I make use of the nlme package and the weigths-parameter. Let's say that I hypothesize that the exam score of students (normexam) is influenced by their score on a standardized LR test (standLRT). Students are of course nested in "schools". These variables are contained in the

Paul: I may have found the issue (which is similar to your conclusion). I checked using egsingle in the mlmRev package as these individuals are strictly nested in this case: library(mlmRev) library(nlme) fm1 <- lme(math ~ year, random=~1|schoolid/childid, egsingle) fm2 <- lmer(math ~ year +(1|schoolid:childid) + (1|schoolid), egsingle) Checking the summary of both models, the output is

Hi All, I'm trying to add a 'rug' representation of my data to a plot created with densityplot(). While I can do this in the simple case, I can't do it properly when I include the "groups" argument. I have an example below. I am running a reasonably new version of R. print(sessionInfo()) R version 2.12.0 Patched (2010-11-07 r53537) Platform: i686-pc-linux-gnu

In the course of exploring response prediction, I stumbled upon a small discrepancy between the CIs produced by predict.lm() and all.effects() require(mlmRev) require(effects) hsb.lm <- lm(mAch ~ minrty * sector, Hsb82) hsb.new <- data.frame( minrty = rep(c('No', 'Yes'), 2), sector = rep(c('Public', 'Catholic'), each = 2)) hsb.eff <-

Hi R users! I am trying to learn some multilevel analysis, but unfortunately i am now very confused. The reason: http://www.ats.ucla.edu/stat/hlm/seminars/hlm_mlm/mlm_hlm_seminar.htm http://www.ats.ucla.edu/stat/sas/seminars/sas_mlm/mlm_sas_seminar.htm and MlmSoftRev. pdf from mlmRev package. >From what i see, the first two links seem to declare the level one variable as a random part (i

Dear community, I am looking for a possibility to draw 'regression lines' instead of 'smooth' lines in grouped xyplots. The following code should give you a small example of the data structure. library(lattice) data(Gcsemv, package = "mlmRev") # Creates artificial grouping variable ... Gcsemv$Groups <- ifelse(as.numeric(as.character(Gcsemv$school))>65000,

Hello. I am having trouble downloading the lme4 package from the CRAN site. The error is: > local({a <- CRAN.packages() + install.packages(select.list(a[,1],,TRUE), .libPaths()[1], available=a, dependencies=TRUE)}) trying URL `http://cran.r-project.org/bin/windows/contrib/2.0/PACKAGES' Content type `text/plain; charset=iso-8859-1' length 26129 bytes opened URL downloaded 25Kb

Hi, I'm making a multipanel lattice densityplot figure with 2 factors (3 and 20 classes in each factor) with the following statement (the type="percent" is there to prevent plotting the actual points which detract from the figure - is there another way of doing this?): densityplot(~End-Begin | Type * Chromosome, data=Mon, layout=c(5,12), xlab="Element

Hi everyone, Using R 2.10.1 on Windows Vista. DOWNLOADED PACKAGES DO NOT INSTALL. I expect to see them in C:\Program Files\R\R-2.10.1\library These files download (see below). And they are all in zip format. What am I doing wrong? Please help. All suggestions appreciated. trying URL 'http://cran.cnr.Berkeley.edu/bin/windows/contrib/2.10/RColorBrewer_1.0-2.zip' Content type

Dear all, Can anyone help me, my R software can not run a nested linear regression by using the lme funcion. The message that appears is  Error: could not find function "lme" I already downloaded and loaded the package, please see below. Thank you in advance for any help! Nadia. > data<-read.csv("/Users/nadiasan1/Desktop/MOE and MOR.csv")> attach(data)>

I posted this on R help, and a few others responded indicating they too were able to replicate the error as a function of missing data. I believe this should not be the case and hence and reporting it here. ### Code provided on R-Help by Ivar Herfindal # Simulate data testdata <- cbind.data.frame(gr=3Drep(letters[1:4], each=3D5), = aa=3Drnorm(20), bb=3Drnorm(20)) # Introduce some missingness

Hi all, I'm trying to get a vertical line at a specific point in a densityplot. abline seems to be what's required, but it doesn't align itself to the scale used in the plot. example: library(lattice) x<-rnorm(100) plot.new() densityplot(x) abline(v=0) ----- The line seems to use some other coordinate system. What kind of call do I use to make abline use the graph's

I'm trying to use a lattice function within a function and have problems passing the "groups" argument properly. Let's say I have a data frame d <- data.frame(x = rnorm(100), y = c("a", "b")) and want to plot variable x in a densityplot, grouped by the variable y, then I would do something like densityplot(~ x, d, groups = y) If however I wanted to

Hi, I have created two separate overlapping density plots- see example code below. What I wish now to do is combine them into one figure where they sit side by side. Any help would be great! many thanks in advance, josh. ##################### thedataA <- data.frame(x1=rnorm(100,1,1),x2=rnorm(100,3,1)) #create data thedataA.m<-melt(thedataA) densityplot(~value, thedataA.m,

Hi, I have the following script: ---- t.R --- grafica <- function() { v <- read.csv('preprocessed/komolongma.ece.uprm.edu.active',sep=',') x <- as.ts(v$active) bitmap(file="output.png") densityplot(~x,col='blue',main='Density Plot') dev.off() } grafica() ---- t.R --- When I "sourced" it from R prompt, it quietly runs.

Hi, Can someone please offer a procedure for going from CIs produced by intervals.lme() to fixed-effects response CIs. Here's a simple example: library(mlmRev) library(nlme) hsb.lme <- lme(mAch ~ minrty * sector, random = ~ 1 | cses, Hsb82) (intervals(hsb.lme)) (hsb.new <- data.frame minrty = rep(c('No', 'Yes'), 2), sector = rep(c('Public',