similar to: lme for time series prediction

Hello! I want to calculate the intra- and interrater reliability of my study. The design is very simple, 5 raters rated a diagnostic score 3 times for 19 patients. Are there methods/funtions in R? I only found packages to calculate interrater variability and intraclass correlation coefficients for matrices of n*m (n subjects, m raters) - I have n subjects, m raters and r repetitions. Can

Hi, I'm fitting a relatively simple growth model to some forest plot data. Two species of trees were planted in different mixtures in 10 (nearly-adjacent) plots and measured on four occasions over 10 years. The model is constructed in terms of the diameter increments (per year; DI) in the 3 intervals, in which DI is modelled as a function of mid-interval D and DSQ. The details of the

Using the weight argument with a variance function in lme (nlme), you can allow for heteroscedasticity of the within-group error. Is there a way to do this for the other variance components? For example, suppose you had subjects, days nested within subjects, and visits nested within days within subjects (a fully nested two-way design) and you had, say men and women subjects. Could you allow for

Hey, I was using lme and proc mixed in SAS to run a empirical bayesian model. I used the same method for both lme and proc mixed (the default REML). I got very similar, but not identical results. I am just wondering if anyone knows what the differneces may be between proc mixed and lme. Any thoughts would be appreciated! Thanks, Liz

Dear R-Users I have a problem accessing some values in the output from the summary of an lme fit. I fit the model below: ggg <- lme (ST~ -1 + as.factor(endp):Z.sas + as.factor(endp), data=dat4a, random=~-1 + as.factor(endp) + as.factor(endp):Z.sas|as.factor(trials), correlation = corSymm(form=~1|as.factor(trials)/as.factor(id)), weights=varIdent(form=~1|endp)) hh

I can ask my question using and example from Chapter 1 of Pinheiro & Bates. > # 1.4 An Analysis of Covariance Model > > OrthoFem <- Orthodont[ Orthodont$Sex == "Female", ] > fm1OrthF <- + lme( distance ~ age, data = OrthoFem, random = ~ 1 | Subject ) > summary( fm1OrthF ) Linear mixed-effects model fit by REML Data: OrthoFem AIC BIC

Dear R Users I have difficulties accessing the variance components for an lme fit when the variance covariance matrix of the random effects is not positive definite. Can anyone inform me on how to get by this ? Thanks in advance Pryseley --------------------------------- [[alternative HTML version deleted]]

Dear community, can anyone provide a snippet of code to force the lm() to fit a model with terms in the formula in an arbitrary order? I am interested in something like: lm(y ~ A * B + C, data=data) where the interaction of A and B should be in the formula before C. My goal is to simplify my presentation of models using the anova() statement. I have found that this should be possible using

Hello R-users Is it possible to fit a three level linear mixed effect model in R? If anyone has an idea or sample code, i will appreciate it very much if i can receive it. I am reading the book by Pinheiro and Bates but have not come across that yet! Kind regards Pryseley --------------------------------- [[alternative HTML version deleted]]

hello i have a mixed effect model which gives slope and intercept terms for 6 groups (diagnosis (3 levels) by risk group(2 levels)). the fixed part of the model is -- brain volume ~ Diagnosis + Risk Group + (Risk Group * age : Diagnosis) - 1 thus allowing risk group age/slope terms to vary within diagnosis and omitting a nonsignificant diagnosis by risk group intercept (age was centered)

I am analyzing data from an experiment with two factors: Carbon (+/-) and O3 (+/-), with 4 replicates of each treatment, and 4 harvests over a year. The treatments are assigned in a block design to individual Rings. I have approaches this as a repeated measures design. Fixed factors are Carbon, O3 and Harvest, with Ring assigned as a random variable. I have performed repeated measures analysis

Dear All, How can I sort a data frame (using one of the column)? Thanks for your support. Regards. Abd. Rahman Kassim (PhD) Head Forest Ecology Branch Forest Management & Ecology Program Forestry and Conservation Division Forest Research Institute Malaysia Kepong 52109 Selangor, Malaysia ***************************************** Checked by TrendMicro Interscan Messaging Security. For any

Hi, I have great problems with my work in R. I look for to model the growth of fish. I have "Longitudinal data", a serie of repeated measures for each individual. Using the corresponding packages "nlme" in R. I treat to fit to the data different growth functions, wich were entered by me. Unfortunately for no it was arrived at the convergence, several error messages appeared. I

Dear R community, I'm trying to figure out if there is any way to split the printed output of some commands, for example summary.lme, so that I can intersperse comments in Sweave. I don't mind running the command numerous times and masking various portions of the output, or saving the output as an object and printing it, but I can't figure out how to do either. Does anyone have any

Hello! So, my problem is following. I have bird offspring growth data and I'd like to model individual growth curves (aim is to study asymptotes and inflection points) with nlme according to Pinheiro & Bates 2000: first using nlsList to generate individual curves and then nlme to study the parameters and fixed effects. The data is structured to two levels. I have broods and

Hi all, I need to put two different axis to one plot. On the top of the plot, I need to put one axis, with increments from left side to the right side; then at the bottom of the same plot, I need to put another axis, with increments from right side to the left side and showing a different unit. How do I do that? By the way, is there a "hold" command for plotting? If I first plot a

Hi all, I have collected response time data from 178 participants ('sub') for each combination of 4 within-Ss factors ('con','int','tone','cue'). Additionally, I have recorded the gender of each participant, so this forms a between-Ss factor ('gender'). Normally this would be analyzed using aov:

I have three columns of data, Xc, Trt and fish. This was a repeated measures design with 6 measurements taken from each of 5 fish. Xc is the actual measurement, Trt is the treatment, and fish is the fish number. Data can be seen below (hopefully it is in the column format). I would like to look for differences between treatments in a repeated measures format. I used the following code

Any help would be most appreciated. (Don't make me get down on my hands and knees and beg for help, cause I'll do it!!) My boss has me learning R and doing nested regression with the report due Mon (Friday night statistics...fun. ). Anyway, here's my problem: In a regression equation not accounting for the fact that people are nested in families, the result for Z variable is VERY

Hi, How can I execute some scripts from within R. I have a large data file which I process (for instance with gawk, but not only) before performing some statistics. I would like to do this in R, so that I do not have to save many data files and then making analysis on them (which proved to be unefficient) Thank you Marco Grazzi