search for: multilevels

It is not a pure R question,but I hope some one can give me advices. I want to use analysis my data with the multilevel model.The data has 2 levels---- the second level has 52 units and each second level unit has 19-23 units.I think the sample size is quite small,but just now I can't make the sample size much bigger.So I want to ask if I use the multilevel model to analysis the data set,will

Goodmorning everybody, i'm an italian statistician and i'm using R for research. Could someone tell me some indices to see the goodness of fit in multilevel modelling? I'm using the lmer function, and I want to know if my model fit well my data. I actually want to justify the use of multilevel model instead the classical one. Hope someone can help me. Thank you. Greetings

Dear all, I am struggling with a problem which I have been reading on the forums about and it did not seem to me that there is a precise answer to my question. However, I still hope there is one. I am working with http://timss.bc.edu/ PIRLS data and trying to conduct multilevel analysis. There are different weights for each level of analysis in the PIRLS dataset (e.g. there is a school

I am using a multilevel modeling approach to model change in a person's symptom score over time (i.e., longitudinal individual growth models). I have been using the lme function in the multilevel package for the analyses, but my problem is that my outcome (symptoms) and one of my predictors (events) are count data, and are non-normal. Do you have any suggestions for how to deal with them?

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,

Hi, does anyone out there have a recommendation for multilevel / random effects and longitudinal analysis? My dream book would be something that's both accessible to a non-statistician but rigorous (because I seem to be slowly turning into a statistician) and ideally would use R. Peter

Hi, I'm trying to reshape my data set from wide to tall format for multilevel modeling. Unfortunately, the function I typically use (make.univ from the multilevel package) does not appear to work with unbalanced data frames, which is what I'm dealing with. Below is an example of the columns of a data frame similar to what I'm working with: ID a1 a2 a4 b2 b3 b4 b5 b6 Below

Hi R folks (Dr. Bates in particular), In August 2005, Dr. Bates mentioned that the documentation for lme4 "will be in the form of a book with the working title 'Multilevel Modeling in R'" and I'm just wondering if there is an estimated date of publication or if it's still a long way off. The Rnews article does a great job of introducing the package, but I'm

Hello -- I am curious if lmer can be used to fit a multilevel factor model such as a two-parameter item response model. The one parameter model is straightforward. A two-factor model requires a set of factor loadings multiplying a single random effect. For example, a logit model for the ith subject responding correctly to the jth item (j=1,..,J) is logit[p(ij)] = a1*item1(i) + ... + aJ *

Hello everyone, I am employing the waba method from the multilevel package for obtaining a within-group correlation (Description: http://bg9.imslab.co.jp/Rhelp/R-2.4.0/src/library/multilevel/man/waba.html). Does anybody know a way or a calculation for obtaining a significance value for that correlation? And another question: Does anybody know whether it is possible to save individual

Dear All, does anybody know of a package (working under Linux) for multilevel IRT modelling? I'd love to do this without having to go on WINSTEPS or the like.. thanks for the attention! Federico Andreis ----- Dr. Federico Andreis Universit? degli Studi di Milano-Bicocca, PhD Student MEB Department, Karolinska Institutet, Stockholm, Visiting PhD Student -- View this message in context:

Dear ListeRs, I am trying to fit a heteroscedastic multilevel model using lmer{lme4- package). Take, for instance, the (fictive) model below. lmer(test.result ~ homework + Sex -1 + (1 | School)) Suppose that I suspect the error terms in the predicted values to differ between men and women (so, on the first level). In order to model this, I want the 'Sex'-variable to be random on

Dear all, I am trying to replicate some multilevel models with binary outcomes using R's "lmer" and "glmmPQL" and Stata's gllmm, respectively. The data can be found at <http://www.uni-koeln.de/~ahf34/xerop.dta>. The relevant Stata output can be found at <http://www.uni- koeln.de/~ahf34/stataoutput.txt>. First, you will find the unconditional model,

We will present a workshop on "Multilevel Modeling in R" June 18-19, 2003 in Madison, WI, USA. Details are available at http://www.stat.wisc.edu/shortcourse/Rworkshop.html

Hi! I'm pretty raw when working with the R models (linear or not). I'm wondering has anybody worked with the NLME library and dichotomous outcomes. I have a binary outcome variable that I woul like to model in a nested (multilevel) model. I started to fit a logistic model to a NLS function, but could not suceed. I know there are better ways to do it in R with either the LRM or GLM wih

Is there any package developed in R for multilevel (hierarchical) analysis of continuous and categorical dependent variables?

Hello, I have difficulties to deal with multilevel model. My dataset is composed of 10910 observations, 1237 plants nested within 17 stations. The data set is not balanced. Response variable is binary and repeated. I tried to fit this model model<- glmmPQL( y ~ z1.lon*lun + z2.lat*lun + z1.lon*lar + z2.lat*lar + z1.lon*sca + z2.lat*sca +z1.lon*eta + z2.lat*eta, random = ~ lun + lar + sca

Hi Sir I am very new user of R for the research project on multilevel logistic regression. There is confusion about bugs() function in R and BUGS software. Is there any relation between these two? Is there any comprehensive package for Multilevel Logistic modelling in R? Please guide in this regard. Thank You RAZA --------------------------------- Boardwalk for

Hi R users I want to use the lme package for a multilevel analysis on the following example: > math<-c(2, 3,2, 5, 6 ,7 , 7) > sex<-c(1, 2, 1, 2, 2, 2, 1) > school_A<-c(1,1,1,2,2,2,2) > school_B<-c(10,10,10,20,20,20,20) > mydata<-data.frame(math, sex, school_A, school_B) > mydata School_A and school_B are two different school characteristics, math is an

Hello all: I've read the document named "A Brief Introduction to R, the multilevel package and the nlme package". At p68, one can transform the dataset to the required format by using "make.univ". I wanna know,how the new variable "MULTDV" is calculated(can you show me the formula if possible please?)?And what's the usage of this new variable in the following