search for: hlm

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 don't know sas synthax, but i think i am rig...

Dear list members, the following hlm was constructed: hlm <- groupedData(laut ~ design | grpzugeh, data = imp.not.I) the grouped data object is located at and can be downloaded: www.anicca-vijja.de/lg/hlm_example.Rdata The following works: library(nlme) summary( fitlme <- lme(hlm) ) with output: ... AIC BIC...

Dear R-users, I'm running a lmer model using the lme4 package. My dependent variable is dichotomous and I'm using the "binomial" family. The results are slightly different from the HLM results based on a Bernoulli distribution. I read that a Bernoulli distribution is an extension of a binomial distribution. Is that right? If so, how can I adapt my R model to a Bernoulli distribution so that my R results are the same as my HLM results? Thank you so much, Luana Marotta [[altern...

I'm hoping that this is a relatively easy question for someone familiar with the lme4 package. I'm accustomed to using HLM software and writing a simple 2 level [null] equation like this: L1 - Yij = b0 + e L2 - b0 = B00 + u0 The following command in R provides results that are identical to the HLM program. results <- lmer( Y ~ 1 |id , PanelData4) I can't seem to find any examples on-line no...

...ing variables, and time (years) and conflict (MCI.c) as predictors. I have been instructed to include random effects for the slopes of both predictors as well as the intercepts, and then to drop non-significant random effects from the model. The instructor and the rest of the class is using HLM 6.0, which gives p- values for random effects, and the procedure is simply to run a model, note which random effects are not significant, and drop them from the model. I was hoping I could to something analogous by using the anova function to compare models with and without a particular rand...

...l; model score = trt pair grade school/ solution covb ddfm=bw ; random int / sub=team solution type=un; run; I have tried both lmer and hglm, but non of them works. Could anyone tell me how can I covert this SAS codes to R? Thanks -- View this message in context: http://r.789695.n4.nabble.com/HLM-Model-tp3242999p3242999.html Sent from the R help mailing list archive at Nabble.com.

Does anyone know of code to conduct hierarchical (that is, multi-level) models using R. Beyond simply requiring a nested design, I want to model explicitly the covariance between levels as is done in such multi-level modeling software as HLM or MLwin and discussed in Goldestein (1999) available online at http://www.arnoldpublishers.com/support/goldstein.htm (a nice and free resource for anyone interested in HLM). The work that I will be doing in the immediate future would involve linear applications of multi-level modeling, however I...

Full_Name: Zivan Karaman Version: 2.7.2 OS: Windows XP Submission from: (NULL) (195.6.68.214) I'm puzzled by the readRegistry function. Shouldn't the "hive" argument be something like c("HLM", "HCR", "HCU", "HU", "HCC", "HPD") rather than c("HLM", "HCR", "HCU", "HU", "HCC, HPD"). For example, > readRegistry("Test", "HCC, HPD") Error in readRegistry("Te...

Hello dear uesRs, I am working on modeling both level one and level two heteroscedasticity in HLM. In my model, both error variance and variance of random intercept / random slope are affected by some level two variables. I found that nlme is able to model heteroscedasticity. I learned how to use it for level one heteroscedasticity but don't know how to use it to model the level tw...

...sig-ME mailing list is where this question would have been on-topic. -- Sent from my phone. Please excuse my brevity. On August 16, 2017 6:17:03 AM PDT, b88207001 at ntu.edu.tw wrote: >Hello dear uesRs, > >I am working on modeling both level one and level two >heteroscedasticity in HLM. In my model, both error variance and >variance of random intercept / random slope are affected by some level > >two variables. > >I found that nlme is able to model heteroscedasticity. I learned how >to use it for level one heteroscedasticity but don't know how to use...

...nd sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed, Aug 16, 2017 at 6:17 AM, <b88207001 at ntu.edu.tw> wrote: > Hello dear uesRs, > > I am working on modeling both level one and level two heteroscedasticity in > HLM. In my model, both error variance and variance of random intercept / > random slope are affected by some level two variables. > > I found that nlme is able to model heteroscedasticity. I learned how to use > it for level one heteroscedasticity but don't know how to use it to model &...

...use R for this also. I've searched the list archives, and consulted the one-line version of Pinheiro and Bates (available through my library), but I'm having a great deal of difficulty translating what I'm learning in class into lmer syntax. Specifically, the instructor is using HLM 6.0. In this program, one specifies the level one and level two models explicitly, and I'm having trouble understanding what the equivalent of this is in lmer. Most of the examples we cover in class are change models, i.e., we working with longitudinal data. Specific questions: in HLM...

..., Brett wrote: > > > Does anyone know of code to conduct hierarchical (that is, multi-level) > > models using R. Beyond simply requiring a nested design, I want to model > > explicitly the covariance between levels as is done in such multi-level > > modeling software as HLM or MLwin and discussed in Goldestein (1999) > > The lme() function in the nlme package will fit most of these linear > hierarchical models. > > There is code in Jim Lindsey's 'repeated' package (his page is linked from > CRAN) for generalised linear models with rando...

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. Howev...

Dear R-helpers, I'm analyzing a data with hierarchical linear model. I have one level 1 predictor and one level 2 predictor, which looks like below: fm1 <- lmer(y ~ 1 + x1 + x2 + x1:x2 + (1 + x1 | id.full)) where: y is the outcome variable. x1 is the level 1 predictor variable. x2 is the level 2 predictor variable. id.full is the conditioned variable. It runs beautifully when only x1

HLM question? Is there a minmum number of observations required for a category..I have individusals in work teams.I have incomplete data for all the teams ..sometimes I only have data for one person in a team.I assume that HLM can't work here! But what would be the mimimal.at the moment I have...

I have successfully installed R (version 2.8.1) and RMySQL (version 0.7-4) on my PC (Windows). Now I have a problem running RMySQL on R. I constantly receive the following error-message: Error in utils::readRegistry("SOFTWARE\\MySQL AB", hive = "HLM", maxdepth = 2) : Registry-Schl?ssel 'S' nicht gefunden Error : .onLoad in 'loadNamespace' f?r 'RMySQL' fehlgeschlagen Fehler: Laden von Paket/Namensraum f?r 'RMySQL' fehlgeschlagen Does anyone have a clue what I should do? I don`t have any experience in s...

Hi everyone, I need to get a between-component variance (e.g. random effects Anova), but using lmer I don't get the same results (variance component) than using random effects Anova. I am using a database of students, clustered on schools (there is not the same number of students by school). According to the ICC1 command, the interclass correlation is .44 > ICC1(anova1) [1] 0.4414491

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

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