similar to: NLME plottting and Confidence Intervals

I am analyzing a dataset on the effects of six pesticides on population growth rate of a predatory mite. The response variable is the population growth rate of the mite (ranges from negative to positive) and the exploratory variable is a categorical variable (treatment). The experiment was blocked in time (3 blocks / replicates per block) and it is unbalanced - at least 1 replicate per block. I am

Hello, I am interested in using nlme to model repeated measurements, but I don't seem to get good CIs. With the code below I tried to generate data sets according to the model given by equations (1.4) and (1.5) on pages 7 and 8 of Pinheiro and Bates 2000 (having chosen values for beta, sigma.b and sigma similar to those estimated in the text). For each data set I used lme() to fit a model,

Dear members of the R-Help Team, we are reaching out to you with a question regarding using intervals()<https://www.rdocumentation.org/packages/nlme/versions/3.1-163/topics/intervals> to create inference for nlme()<https://www.rdocumentation.org/packages/nlme/versions/3.1-164/topics/nlme> function. The maintainer for the nlme package is listed as the R-Core Team and we were advised

Dear Ivan, thanks for the insights! This points us directly in the direction we need. Have a lovely day! Yours sincerely, Tatiana, Marvin & Paul from Statistics Lab ________________________________ From: Ivan Krylov <ikrylov at disroot.org> Sent: Monday, May 6, 2024 4:24 PM To: Bielakova Tatiana Cc: R-help at r-project.org; Stephan Paul Andreas Kurt; Lob Marvin Subject: Re: [R]

Hi I use gnls to fit non linear models of the form y = alpha * x**beta (alpha and beta being linear functions of a 2nd regressor z i.e. alpha=a1+a2*z and beta=b1+b2*z) with variance function varPower(fitted(.)) which sounds correct for the data set I use. My purpose is to use the fitted models for predictions with other sets of regressors x, z than those used in fitting. I therefore need to

I want to compute confidence intervals for the random effect estimates for each subject. From checking on postings, this is what I cobbled together using Orthodont data.frame as an example. There was some discussion of how to properly access lmer slots and bVar, but I'm not sure I understood. Is the approach shown below correct? Rick B. # Orthodont is from nlme (can't have both nlme and

I am using lme from the nlme package to fit a mixed model. We have observations nested in patients(encounters) and patients nested in groups (2 different treatments). We are interested in the differences between the 2 groups, both the means and the standard deviations (are patients in group A less variable than those in group B? both within patient and between patient within group). Here is

Dear All, I would like to be able to estimate confidence intervals for a linear combination of coefficients for a GLS model. I am familiar with John Foxton's helpful paper on Time Series Regression and Generalised Least Squares (GLS) and have learnt a bit about the gls function. I have downloaded the gmodels package so I can use the estimable function. The estimable function is very

I'm fairly new to R and am wondering if anybody knows of R code to calculate confidence intervals for parameters (fixed effects and variance components) from mixed effects models based on Sattherthwaite's method? I'm also interested in Satterthwaite-based confidence intervals for linear combinations (mostly sums) of various variance components. [[alternative HTML version

Dear listers, As an exercise, I am trying to fit a logistic model with nlme. Blue tit pulli (youngs) were weighted occasionnally (for field reasons) along time in 17 nestboxes. Individuals where not idenfied but their age was known. This means that for a given age several measurements were done but individuals could not be identified from a time to the other. This makes repeated values for

Dear R Helpers, I try to write a small package that based on nlme however my code does not work. R always appears this message: Error in eval(expr, envir, enclos) : object "y" not found where y is the response variable. Please help me out! This is my code: require(nlme) AMPmixed<-function(y, x, S1=c("asymptotic","logistic"), random,data,

Gday, This is a repost since I only had one direct reply and I remain mystified- This may be stupidity on my part but it may not be so simple. In brief, my problem is I'm not sure how to extract parameter values/effect sizes from a nonlinear regression model with a significant interaction term. My data sets are dose response curves (force and dose) for muscle that also have two

Jos?? C. Pinheiro Training in UK - Analyzing Mixed-Effects Models with S-PLUS Mixed-effects models provide a powerful tool for analyzing grouped data. This course will overview the application of linear and nonlinear mixed-effects models in the analysis of grouped data, using the NLME software in S-PLUS to illustrate the different stages of model fitting. A new element to the course will cover

Dear all, &nbsp; Is there a function to calculate the&nbsp; prediction intervals for random effects in non-linear mixed models? I found a way to do it for linear mixed models but not for non-linear&nbsp;mixed one. &nbsp; Many thnaks &nbsp; Bernard &nbsp; &nbsp; _____________________________________________________________________________ o.fr [[alternative

I'm applying logistic regression to a moderate sized data set for which I believe Wald based confidence intervals on B coefficients are too conservative. Some of the literature recommends using confidence intervals based on the likelihood ratio in such cases, but I'm having difficulty locating a package that can do these. Any help would be immensely appreciated. Best, Jeff Hanna --

Hello all. I was wondering if there is a way to hold constant the fixed effects correlation structure across multiple groups? For example, I have two groups and I fit a three parameter logistic growth curve where the fixed effects are free to vary across the groups. I'll paste in the code as a concrete example: > Result.NLME <- nlme(Score ~ SSlogis(Time, Asym, xmid, scal), +

I am analyzing a dataset on the effects of six pesticides on population growth rate of a predatory mite. The response variable is the population growth rate of the mite expressed as ln(Nfinal/Nstarting) of the mite, where N final the population of the mite at the end of the experiment and N starting the population of the mite at the beginning of the experiment. Each of the six treatments was ran

Hi, Sorry for repeated question. I performed logistic regression using lrm and penalized it with pentrace function. I wanted to get confidence intervals of odds ratio of each predictor and summary(MyModel) gave them. I also tried to get bootstrapping standard errors in the logistic regression. bootcov function in rms package provided them. Then, I found that the confidence intervals provided by

Hi... I have to use R to find out the 90% confidence-interval for the sensitivity and specificity of the following diagnostic test: A particular diagnostic test for multiple sclerosis was conducted on 20 MS patients and 20 healthy subjects, 6 MS patients were classified as healthy and 8 healthy subjects were classified as suffering from the MS. Furthermore, I need to find the number of MS

Hi, I found myself trying to figure out the type of confidence interval used for the coefficients of the logistic regression fit by using glm(family=binomial)... I suspect it is Wald confidence interval but am not sure...Does anybody know? Also, if so, how can I ask for likelihood ratio and/or score-based confidence intervals? Yours, Michael ~~~~~~~~~~~~~~~~~~~~~ Michael Levine Assistant