similar to: Doubly Multivariate LME

Dear List: I have a data set with over 7000 students with about 4 observations over time per student. I want to examine the within-group fits of a random sample of this group as it takes forever to compute and draw all 7000 regressions. Here is the code I have used so far. >group<-groupedData(math~year|childid, data=scores) >group.list<-lmList(group)

Dear list In HLM, one can specify a covariate at one of the "levels". For example, if the data structure are repeated observations nested within students nested within schools, school size might be a covariate that is used at level 3, but not at the other levels. In HLM this is rather easy to do. However, how can one specify a covariate in R for only one of the levels? I have a

I am learning about sparse matrices and wonder if R can create them from a full matrix. Can anyone tell me how I might be able to accomplish this. ------ Harold C. Doran Director of Research and Evaluation New American Schools 675 N. Washington Street, Suite 220 Alexandria, Virginia 22314 703.647.1628 <http://www.edperform.net/> [[alternate HTML version deleted]]

Dear R: Am I having trouble downloading the LME4 library. I am using Windows and am using ver 1.7 I have tried the following: 1) Install package from CRAN, but LME4 is not listed 2) Downloaded LME4 from http://cran.us.r-project.org/, however, I cannot open the file when I try install from local drive. I get the following error: Error in file(file, "r") : unable to open connection

Dear List: I am having difficulties with the fitted values at different levels of a multilevel model. My data set is a series of student test scores over time with a total of 7,280 observations, 1,720 students nested witin 60 schools. The data set is not balanced. The model was fit using eg.model.1<-lme(math~year, random=~year|schoolid/childid, data=single). When I call the random

Dear List: I am trying to find the area between two ECDFs. I am examining the gap in performance between two groups, males and females on a student achievement test in math, which is a continuous metric. I start by creating a subset of the dataframe male<-subset(datafile, female="Male") female<-subset(datafile, female="Female") I then plot the two CDFs via

Dear List I have math test scores for male and female students where gender is a dummy code (female =1). I also have a variety of other demographic variables. However to begin, I want to create a very simple stripchart where female math scores are a blue circle and male scores are a red triangle. I am having difficulty using conditional statements to accomplish this. Thank you. ------

Dear List: I am trying to figure out how to incorporate measurement error in an longitudinal educational data set using lme to create a "true score" model. As a by-product of the procedures used to scale educational tests, one can obtain a person-specific measurement error associated with each score, or a conditional standard error. For example, a score of 200 would have measurement

I am trying to import a file using R Commander. It was working a few days ago, but now I get the following message when I try to import from SPSS. Any thoughts? Error in parse(file, n, text, prompt) : parse error ------ Harold C. Doran Director of Research and Evaluation New American Schools 675 N. Washington Street, Suite 220 Alexandria, Virginia 22314 703.647.1628

I am new to R and would like to get some practice analyzing multilevel data. I wonder if anyone can point me to a sample data set and command lines that I might replicate for a sample session. I would then compare my output with HLM output. Any help is appreciated. ------ Harold C. Doran Director of Research and Evaluation New American Schools 675 N. Washington Street, Suite 220 Alexandria,

I have loaded the foreign package and am still having problems with an import. I get a message that reads, unable to open file. Whe I try different files I get the same message. Here is the code I used. Am I missing something? I am using 1.7 and have also tried this in 1.6 with the same problem. hsb<-read.spss("C:\HLM504_Student\Examples\AppendxA\HSB1.SAV", use.value.labels=TRUE,

Have a look at ?optim. I don't think it has the BHHH algorithm as an option, though. =========================================== David Barron Jesus College University of Oxford -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Harold Doran Sent: 10 July 2003 15:43 To: Fohr, Marc [AM]; R-help at stat.math.ethz.ch

20 subjects were measured in 5 conditions (thus repeated measures) and for each subject in each condition there are 4 response measures (thus multivariate as it is a combined score that needs to be compared across the conditions). So, using a multivariate approach to repeated measures this is a doubly multivariate analysis. I would appreciate any suggestions as to the best way to do such a

Hello, I am switching from SPSS-Windows to R-Linux. My university is very SPSS-oriented so maybe that's the cause of my problems. I am a beginner in R and my assignments are SPSS-oriented, so I hope I don't annoy anyone with my questions... Right now I've got 2 problems: -I have to evaluate discriminant functions I have calculated with lda(MASS). I can't find a measure that

Hi, I would like to see if a matching variable is an effect-modifier in a conditional logistic regression. Naturally, the matching variable can't enter directly in the model but as an interaction with terms that are in. However, I have problems in formulating the correct model the term that's already in the model is a factor. I am using treatment contrasts and the problem is that if I

This question comes up periodically, probably enough to give it a proper thread and maybe point to this thread for reference (similar to the 'conservative anova' thread not too long ago). Moving from lme syntax, which is the function found in the nlme package, to lmer syntax (found in lme4) is not too difficult. It is probably useful to first explain what the differences are between the

Dear list: I am trying to merge two files together from output I get based on the coef() command. Here is what I am running into. I have two simple linear mixed models > mod1.lme<-lme(math~year, data=sample, random=~year|childid/schoolid) > mod2.lme<-lme(math~year, data=sample, random=~year|childid) I then call the coefficients and store them in the following objects using >

Dear listers, I can't find the variance or se of the coefficients in a multilevel model using lme. I want to calculate a Chi square test statistics for the variability of the coefficients across levels. I have a simple 2-level problem, where I want to check weather a certain covariate varies across level 2 units. Pinheiro Bates suggest just looking at the intervals or doing a rather

Wayne, Hello, I saw a post of yours out on samba.org and was wondering if you might be able to shed a little light on a problem I'm having with rsync. My rsync source files are all off of nfs mounts and the destination directories are all nfs mounts. The owner and groups all end up as nobody/nobody on the destination, despite being all sorts of owners and groups on the source. Have you

On 07/13/2018 09:03 AM, mark wrote: > Johnny Hughes wrote: >> On 07/13/2018 02:36 AM, Nicolas Kovacs wrote: >> >>> Le 12/07/2018 ? 16:36, mark a ?crit : >>> >>>> I just updated the "critical" firefox update, and it is *seriously* >>>> buggy. >>> > <snip> > >> Well .. it is working like the upstream one,