similar to: glmmPQL probelm

Dear listers, I have two questions: (1) Is there a way in R to change the base-n of the calculations. I wnat to run some calculations either in binary (base-2) or base-4. Is there a way to specify that in R - to chnage from the decimal? (2) I also want to extract the digits from a larger number and store them as a vector. I could do it through converting top string, parsing the string and

HI all, I might add some more information in order to possibly solve my problem. I'm really stuck and no obvious solutions do the trick. I'm using R 1.7.1 on Windows 2000 with the packages regurarly updated. I'm using hypothetical data constructed as a pseudo population conforming to a certain Var-Cov structure. I might add that just > predict(level2) works. But when I add the

Hi! I am a relatively new user of R and I use it to prepare my dissertation. I have come to some very usefull and specific libraries written for S-PLUS 4 and would like to use them in R. Is that possible? I just found out that one of these libraries has already been transfered to R, while 3 others have not. For the matter of beeing more exact I''m interested in the dealing with missing

Dear listers, I must first say that all the suggestions and help I got from the list so far was of great help to my work. I approach you with another question. Is it possible to generate an automatic specification of the formula for lme (or other models in R)? Let me clarify. I'm using models in a simulation run and can have variable number of variables in the data. I would like to generate

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

Hi listers, In light with the recent discussion on the optimizing the use of memory in straneous proceudres i present you m problem, and hope to some additional ideas. I'm running a simualtion that in each step uses quite an amount of memory (but not exceedingly) - just to give you an idea - I create a pseudo population (n=1000, m=3) run lme and lm model and multiply impute (M=5) and do the

Dear listers, I would like to get the bootstrap estimates form my lme model. I have an HLM (multillevel) 2-level model with the dichotomous outcome. I used glmmPQL procedure. However I have a problem since I have a rather unbalanced proportion (90-99% of events, i.e. ones and only 1-10% of nonevents - zeros) although sample sizes are not that small between 500 and 1000 I get pretty weird and

Hi All, I need to fit a mutlivariate normal model to a dataset in order to obtain the mean and covariance parameters. I see that the MVN function in the MCLUST package can do this, however when I try to run even the simplest example provided in the documentation, as below, I get the following error: n <- 1000 set.seed(0) x <- rnorm(n, mean = -1, sd = 2) mvn(modelName = "X", x)

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

Hi, I'm having trouble with glmmPQL from the MASS package. I'm trying to fit a model with a binary response variable, two fixed and two random variables (nested), with a sample of about 200,000 data points. Unfortunately, I'm getting an error message that is difficult to understand without knowing the internals of the glmmPQL function. > model <- glmmPQL(primed ~

Dear listers, I experinced a problem prdicting the values using the LME with multilevel data. I have NA's in my dependent variable and the model is fitted only on the completed cases. I want to estimate the predicted values for the rest of the data (those cases with missing dep. variable) I extracted a subset from the original file containing the variables used in the model as well as the

I've got a PhD student starting this year. She'll be working on data mining. She has asked for a reading list while she's still in her home country, which is a really good sign. Her cosupervisor and I don't (think we) have any problem with choosing things that are specifically about data mining, but there are some statistical ideas (sampling, exploratory-vs-confirmatory,

Dear list, I am trying to use the 'mvrnorm' function from the MASS package for simulating multivariate Gaussian data with given covariance matrix. The diagonal elements of my covariance matrix should be the same, i.e., all variables have the same marginal variance. Also all correlations between all pair of variables should be identical, but could be any value in [-1,1]. The problem I am

Hi , I am programming on a windows system and have problems using notepad which is my main editor.Each time I try to open the editor from the R IDE, R crashes. So I always have to copy my codes from notepad and paste in R to run them. CAn someone tell me if I am doing anything wrong or is there a better editor(freeware) which I could get. thanks cilver ===== ===================== Sylvie B.

Dear R-ers, I am having trouble understanding why I am getting an error using glmmPQL (library MASS). I am getting the following error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 The long story: I have data from an experiment on pairwise comparisons between 3 treatments (a, b, c). So a typical run of an experiment

I'm using glmmPQL, and I still have a few problems with it. In addition to the issue reported earlier, I'm getting the following error and I was wondering if there's something I can do about it. Error in logLik.reStruct(object, conLin) : Na/NaN/Inf in foreign function call (arg 3) ... Warnings: 1: Singular precistion matrix in level -1, block 4 (...) 4: "" The

Dear R users, I'm attempting to fit a GLM with random effects using the tweedie family for the error structure. I'm getting the error: iteration 1 Error in logLik.reStruct(object, conLin) : NA/NaN/Inf in foreign function call (arg 3) I'm running V2.1.0 I notice from searching the lists that the same error was reported in May 2004 by Spencer Graves, but no-one was able to

Can anyone shed any light on this? > doubt.demographic.pql<-glmmPQL(random = ~ 1 | groupid/participantid, + fixed = r.info.doubt ~ + realage + minority + female + education + income + scenario, + data = fgdata.df[coded.resource,], + na.action=na.omit, +

Dear all, I try to fit a glmmPQL on a huge data with 384189 individuals id=1:384189: working in 1520 establishments est:1:1516. The minimum number of individuals in every establishment is 30. This works for a subsample excluding establishemnet cells smaller than 100, but fail when we include smaller cells: R> summary(glmmPQL(count ~ + I( age-ave(age,est) )* ave(age,est) + + I(

I'm getting a strange error from glmmPQL. Consider the following sample code: set.seed(8) N. <- 1000 z <- rnorm(N.) pr.good <- exp(-1e-4*exp(2+2*z)) quantile(pr.good) DF. <- data.frame(yield=rbinom(N., N., pr.good)/N., Offset=rep(-10, N.), nest=1:N.) fit <- glmmPQL(fixed=1-yield~offset(Offset), random=~1|nest, family=binomial(link="cloglog"),