similar to: treatment effects with lme (repeated measurements)

Hello fellow R users, I am having a problem finding the estimates for some overall treatment effects for my mixed models using 'lme' (package nlme). I hope someone can help. Firstly then, the model: The data: Plant biomass (log transformed) Fixed Factors: Treatment(x3 Dry, Wet, Control) Year(x8 2002-2009) Random Factors: 5 plots per treatment, 5 quadrats per plot (N=594 (3*5*5*8)

Hi, I have what I believe is a repeated-measures dataset that I'm trying to analyze using lme(). This is *not* homework, but an exercise in my trying to self-teach myself repeated-measure ANOVA for other *real* datasets that I have and that are extremely similar to the following design. I'm fairly sure the dataset described below would work with lme() -- but it'd be great if anybody

Dear All, I have data in HDF file format and would like to read it into R. I have tried the package hdf5 without success. Any ideas and suggestions?? Kind regards, Katrin -- Katrin Fleischer Vrije Universiteit Amsterdam Faculty of Earth and Life Sciences Subdepartment Hydrolgy and Geo-Environmental Sciences Room E-360 De Boelelaan 1085 1081 HV AMSTERDAM Tel: +31 20 59 87391

Hallo! I have two groups (placebo/verum), every subject is measured at 5 times, the first time t0 is the baseline measurement, t1 to t4 are the measurements after applying the medication (placebo or verum). The question is, if there is a significant difference in the two groups and how large the differnce is (95% confidence intervals). Let me give sample data # Data

Dear All, I have a raster map of the class 'SpatialPointsDataFrame' and coordinates of the class 'SpatialPoints'. I would like to retrieve the values that are contained in the raster map at the specific locations given by the coordinates. Can anyone help me out? Kind regards, Katrin Fleischer

Hi list I am just beginning to understand the complexities of linear mixed effects models. Maybe someone can give advise concerning the following problem: I have two groups of surgical patients in which repeated laboratory measurements were taken over time after surgery. I decided that lme would be the best model to fit the data. I already fitted the model lme(logratio ~ gr*I(pod-10) +

I am trying to do a repeated measurement anova using an lme. I have the following variables: -ID, the identification of the individual -trail, with 2 levels -treatment, with 3 -time, measure 5 times the same individual -VCL, the response variable I tried the following in R, within.gr<-groupedData(VCL~time|ID/treatment/time,data=within)

Dear all, I have built glm models based on presences/absences and a number of predictor maps and would like to compute habitat suitability based on the modelled coefficients. I thought this is pretty straight forward and wanted to use predict() and supply the new data in a data frame, with one column for each predictor. However, I do get an error msg warning me that the number of rows for

I am using lme to handle repeated measurements. So far i can follow the examples from the book from pinheiro and bates. Now i get the problem , that i have "nested" repeated measuremnts, and i cant find out how to do the grouping part of the lme formula. 1.The simple problem ist that i have different Samples , from which i make repeated measurements (each sample is measured 6 times) and

Hallo! I have data of the following design: NSubj were measured at Baseline (visit 1) and at 3 following time points (visit 2, visit 3, visit 4). There is or is not a treatment. Most interesting is the question if there is a difference in treatment between the results of visit 4 and baseline. (The other time points are also of interest.) The level of significance is alpha=0.0179 (because of an

Dear R Masters, I'm an anesthesiology resident trying to make his way through basic statistics. Recently I have been confronted with longitudinal data in a treatment vs. control analysis. My dataframe is in the form of: subj | group | baseline | time | outcome (long) or subj | group | baseline | time1 |...| time6 | (wide) The measured variable is a continuous one. The null hypothesis in

Hello, I am working in a longitudinal study, with a categorical variable as a dependent variable (alcohol consumption: no use, use, abuse and dependence) with repeated measures (baseline, 1 year, 2 years). Besides I have another variable with two groups: control and experimental. I would like to analyze the evolution in each group, I have though in lme, but I am not sure if I can do an lme with

Hello, I am trying to fit a repeated measures linear mixed model (using lme) but I don't want to include any random effects. I'm having trouble (even after consulting Pinheiro & Bates 2000) figuring out how to specify the repeated measure without including it in the specification of a random effect. My data consist of repeated "counts" in "plots" that I wish

Hi, I have searched the archives and can't quite confirm the answer to this. I appreciate your time... I have 4 treatments (fixed) and I would like to know if there is a significant difference in metal volume (metal) between the treatments. The experiment has 5 blocks (random) in each treatment and no block is repeated across treatments. Within each plot there are varying numbers of

Dear list, I'm trying to fit a multilevel (mixed-effects) model using the lme function (package nlme) in R 2.4.0. As a mixed-effects newbie I'm neither sure about the modeling nor the correct R syntax. My data is structured as follows: For each subject, a quantity Y is measured at a number (>= 2) of time points. Moreover, at time point 0 ("baseline"), a quantity X is

Dear All, I fear that this is a really easy question but I do seem to go around in circles.. I have 2 points on a plot and would like to calculate the slope of the line drawn through these 2 points. that cant be so hard?! Thank you in advance, Katrin -- Katrin Fleischer Vrije Universiteit Amsterdam Faculty of Earth and Life Sciences Subdepartment Hydrolgy and Geo-Environmental Sciences Room

Hi, I would like to know if there's a way to detect the workgroup of my own server with libsmbclient. With earlier versions than 3.0.20 it was possible to use smbctx->workgroup after the context was initialized. Since 3.0.15pre2 or so its always "WORKGROUP". Am I missing something? Regards, Gerd Fleischer ______________________________________________________________

Dear R folk, First off I want to thank those of you who responded with comments for my R quick and dirty stats tutorial. They've been quite helpful, and I'm in the process of revising them. When it comes to repeated measures MANOVA, I'm in a bit of a bind, however. I'm beginning to see that all of the documentation is written for psychologists, who have a slightly

Dear List, This is my first post, and I'm a relatively new R user trying to work out a mixed effects model using lme() with random effects, and a correlation structure, and have looked over the archives, & R help on lme, corClasses, & etc extensively for clues. My programming experience is minimal (1 semester of C). My mentor, who has much more programming experience, but a comparable

Hi, The data (attached) I am looking at consists of measurements of growth rate at different ages, for individuals in two treatments (control and infected). What I want to know is whether and when (what age) the growth rate of infected individuals is higher than the growth rate for control individuals. The simplest way to approach this question is to just do a t-test at each age, but because