similar to: Newbie HLM with lme4 questions

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, Is there any package that I can use to simulate the Gaussian Mixture Model , which is a mixture modeling method that is widely used in statistical learning theory. I know there is a mclust, however, I think it is a little bit different from my problem. Thanks very much.. regards. -------------------------- Peng Jiang ?? Ph.D. Candidate Antai College of Economics &

Dear helpers, I wrote a code which estimates a multi-equation model with generalized least squares (GLS). I can use GLS because I know the covariance matrix of the residuals a priori. However, it is a bit slow and I wonder if anybody would be able to point out a way to make it faster (it is part of a bigger code and needs to run several times). Any suggestion would be greatly appreciated. Carlo

Hello there, I am trying to fit an exponential fit using Least squares to some data. #data x <- c(1 ,10, 20, 30, 40, 50, 60, 70, 80, 90, 100) y <- c(0.033823, 0.014779, 0.004698, 0.001584, -0.002017, -0.003436, -0.000006, -0.004626, -0.004626, -0.004626, -0.004626) sub <- data.frame(x,y) #If model is y = a*exp(-x) + b then fit <- nls(y ~ a*exp(-x) + b, data = sub, start

I am fitting models to the responses to a questionnaire that has seven yes/no questions (Item). For each combination of Subject and Item, the variable Response is coded as 0 or 1. I want to include random effects for both Subject and Item. While I understand that the datasets are fairly small, and there are a lot of invariant subjects, I do not understand something that is happening

Is there an element-by-element multiplication in R, like the .* operator in Matlab? eg: A (2x3) B (2x3) C=A.*B C (2x3) C = [[a11*b11 a12*b12 a13*b13]; [a21*b21 a22*b22 a23*b23]] I can't find one... Thanks -Mike Gates

Hello fellow R people, I can not figure out a pretty way to use strplit with vectors Imagine that I got the following data from someone with ID's representing several factors ID data A1-B1-t1 0 A1-B1-t2 1 A1-B2-t1 5 A1-B2-t2 10 A1-B10-t1 0 A1-B10-t2 1 A1-B20-t1 5 A1-B20-t2 10 ... I would like to turn this dataframe to station substation time data A1 B1 t1 0 A1 B1 t2 1 A1 B2 t1 5

Dear all: I'm trying to fit the optimal Box-Cox transformation related to nls (see the code below) for the demand of money data in Green (3th Edition) but in the last step R gives the next error message. Error en `[.data.frame`(eval(object$data), , as.character(formula(object)[[2]])[2]) : undefined columns selected. ?Any idea to solve the problem? Thanks in advance,

Hi All I am having 2 very long character strings (550chars) and I want to put them as expressions together with c(). The problem is that I also get these double-quotes, as seen below in 'fct'. How can I remove these double-quotes? I tried as.name() but it did not work (because of size?). These are creating trouble with subsequent programs, which I tested with strings that for some

Dear R experts, I am having difficulty using loops productively and would like to please ask for advice. I have a dataframe of ids and groups. I would like to break down the dataframe into groups, find the unique sets of ids, then reassemble. My thought was to use a loop, but I have been unable to finish this loop in a logical way. I would like to find the unique ids for group 1, group 2,

A long formula which is converted using as.character, looses its last part: ``diagonal = 1e-12)'' Shorter formula is ok though. Best, H??vard ************ Browse[2]> formula.str y ~ -1 + b1 + b2 + b3 + b4 + b5 + b6 + b7 + b8 + b9 + b10 + b11 + b12 + b13 + b14 + b15 + b16 + b17 + b18 + b19 + b20 + b21 + b22 + b23 + b24 + b25 + b26 + b27 + b28 + b29 + b30 + b31 + b32 +

Dear R buddies, This weekend I became interested in solving Google Code Jam problems using R. I guess R may work very well in this kind of contests but the input of file has been a problem for me. Take this case for example (http://code.google.com/codejam/contest/dashboard?c=agdjb2RlamFtchALEghjb250ZXN0cxjRzBQM), the files are usually of the form: A(number of lines for group 1) a11 a12 a13 a21

Hi, my data set is data.frame(id, yr, y, l, e, k). I would like to estimate Lee and Schmidts (1993, OUP) model in R. My colleague wrote SAS code as follows: ** procedures for creating dummy variables are omitted ** ** di# and dt# are dummy variables for industry and time ** data a2; merge a1 a2 a; by id yr; proc sysnlin maxit=100 outest=beta2; endogenous y; exogenous l e k

Dear all, I have a question regarding setIs and method dispatch in S4 classes: Consider the following example: ##################################################### ## A02 "contains" A01 by setIs: setClass("A01", representation(a="numeric",b="numeric")) setClass("A02", representation(a="numeric",d="numeric"))

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

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

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

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

I am trying to code the following excel formula in R. a b c Result Formula 1 10 0.1 #N/A IF(B2<20,NA(),C2+IF(ISERROR(D1),0,D1)) 2 20 0.2 0.2 IF(B3<20,NA(),C3+IF(ISERROR(D2),0,D2)) 3 30 0.3 0.5 IF(B4<20,NA(),C4+IF(ISERROR(D3),0,D3)) 4 40

Hi everyone, I have posted a similar question to this list, but I don't get a reply. I really want to solve this problem, so I post it again... I am trying to use R to fit some mixed-effects models for a nested data. The data is a simulated data with 111 subjects. Each subject has 6 waves' data. Below are the first two subjects' data : > simu1[1:12,] Grouped Data: gf ~ age |