similar to: {nlme} Question about modeling Level two heteroscedasticity in HLM

If you don't get a response it is because you did not read the Posting Guide which indicates that the R-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

A better place for this post would be on R's mixed models list: r-sig-mixed-models . Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and 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

Hello everyone, I have been working on a code which simply repeatedly appends a number into a vector and write a file. However, it could not be properly implemented when I use it. It works when I run it line by line. I wonder what is the problem and I appreciate anyone who is willing to help. The function and the example code is attached. Any advice is appreciated! Best, Yen

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

Hello everyone, I know where is wrong. I forget to specify the parameters in my function. Thank you for anyone who was trying to help me! Best, Yen ?? b88207001 at ntu.edu.tw: > Hello everyone, > > It seems that I was not successfully attached the code. Here is the > code. I appreciate any help! > > Best, > Yen > > ?? b88207001 at ntu.edu.tw: > >> Hello

Hello everyone, It seems that I was not successfully attached the code. Here is the code. I appreciate any help! Best, Yen ?? b88207001 at ntu.edu.tw: > Hello everyone, > > I have been working on a code which simply repeatedly appends a > number into a vector and write a file. However, it could not be > properly implemented when I use it. It works when I run it line by

Hello, everyone, There's a problem about zero in R and I really need your help. I have a vector shown as x=c(0.1819711,0.4811463,0.1935151,0.1433675), The sum of this vector is shown as 1 in R, but when I type 1-sum(x), the value is not zero, but -2.220446e-16. I can accept that this value is quite small and could be seen as zero, but there would be a problem when it's not really

Hi, I would like to fit a model for a factorial design that allows for unequal variances in all groups. If I am not mistaken, this can be done in lm by specifying weights. A function intended to specify weights for unequal variance structures is provided in the nlme library with the varIdent function. Is it apropriate to use these weights with lm? If not, is there another possibility to do

I would like to estimate the sigma matrix of multinormal distribution through ML. But I don't know how to optimize the parameter sigma. Could any one help me? Thank you so much~ Yen Lee

I'm new to post in R-help and my native language is not English. I apologize if my sentence is not fluent to read. I am doing a simulation study and I need to execute SAS and read a SAS code in R. I try the following code but it doesn't work. system('"c:\\program files\\SAS\\SAS 9.1\\sas.exe" "c:\\syntax.sas"') can anyone give me some help with this?

Dear all, I've written a function and repeated it for 5000 times with loops with different value, and the messages returned are the output I set and 15 warnings. I would like to trace the warnings by stopping the loop when warning came out. Does anyone know how to make it? Thanks a lot for your help. Yen [[alternative HTML version deleted]]

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 logLik 425.3768 465.6087 -197.6884 Random effects:

Dear R listers, I know I'm breaking the rules by asking a "homework" related question-- I hope you'll forgive me. I am a social psychology graduate student, and the only one in my department who uses R. I successfully completed my multiple regression and structural equation modeling courses using R (John Fox's car and sem packages were a big help, as was his book).

Hi, I am currently trying to do a GLMM on a dataset with percent cover of seagrass (dep. var) and a suite of explanatory variables including algal (AC) and epiphyte cover (EC), rainfall, temperature and sunshine hours. M2=glmer(SG~AC+EC+TP+SS+RF+(1|Location/fSi/fTr), family=binomial,data=data,nAGQ=1) As the dependent variable is percent cover, I used a binomial error structure. I also have a

Dear all, Sorry if this is too obvious. I am trying to fit my multiple regression model using lm() Before starting model simplification using step() I checked whether the model presented heteroscedasticity with ncv.test() from the CAR package. It presents it. I want to correct for it, I used hccm() from the CAR package as well and got the Heteroscedasticity-Corrected Covariance Matrix. I am not

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

Hi I am trying to convert SAS codes to R, but some of the result are quite different from SAS. When I ran proc mixed, I have an option ddfm=bw followed by the model. How can I show this method in R?(I am thinking that this maybe the reason that I can't get the similar results) below is my SAS codes: proc mixed data=test covtest empirical; class pair grade team school; model score = trt

Hi all, I tried to do a variance components using nlme, but I got the following warning mesage ##################################################### not meaningful for factors in: Ops.factor(y[revOrder], Fitted) ###################################################### Can someone point out what is the meaning of this warning message? I tried to look at Ops.factor, but I don't

data from multilevel units,first sample the class ,and then the student in calss.following is the 2-level model. and the level-1 model deals with the student,and the level-2 model deals with the class level the students belong to. Level-1 Model Y = B0 + B1*(ZLEAD) + B2*(ZBUL) + B3*(ZSHY) + R Level-2 Model B0 = G00 + U0 B1 = G10 + G11*(ZWARMT) + U1 B2 = G20 + G21*(ZWARMT) + G22*(ZABLET) +

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