similar to: Plotting individual trajectories from individual growth model

I'm trying to understand how to plot individual growth curve trajectories, with the overall mean trajectory superimposed (preferably in a slightly thicker line, maybe in black) over the individual trajectories. Using the sleepstudy data in lme4, here is the code I have so far: library(lme4) library(lattice) xyplot(Reaction ~ Days, data = sleepstudy, group = Subject, type = 'l')

Hello. I have 5 measurement points, my dependent variable is ordinal (0 - 3), and I want to visualize my data. I'm pretty new to R. What I want is to find out whether people with different baseline covariates have different trajectories, so I want a plot with the means trajectory of my dependent variable (the individual points do not make a lot of sense in ordinal data) on each measurement

Am I missing something obvious on how to draw multi-line plots in base graphics? In ggplot2, I can do: data(Oxboys, package = "nlme") library(ggplot2) qplot(age, height, data = Oxboys, geom = "line", group = Subject) But in base graphics, the best I can come up with is this: with(Oxboys, plot(age, height, type = "n")) lapply(split(Oxboys[c("age",

Dear all, I've got a problem in including square variables in lme and lmlist functions. I've tried to work on Oxboys data of Pinheiro and Bates'book, which consist of the heights of 26 boys, each mesured on nine different occasions : > Oxboys Grouped Data: height ~ age | Subject Subject age height Occasion 1 1 -1.0000 140.50 1 2 1 -0.7479 143.40

Hi there, I want to make trajectory plots for data as follows: ID time y 1 1 1.4 1 2 2.0 1 3 2.5 2 1.5 2.3 2 4 4.5 2 5.5 1.6 2 6 2.0 ... That is, I will plot a growth curve for each subject ID, with y in the y axis, and time in the x axis. I would like to have all growth curves in the same plot. Is there

Dear Martin, Have you try to create a new variable for age squared, say agesq? If you fit the model using this new variable you should get the coefficients. So your new model is something like height~age+agesq I hope this helps, Saghir > -----Original Message----- > From: MARTIN Ludovic [SMTP:martinl@mathinfo.ens.univ-reims.fr] > Sent: Wednesday, 07 May, 2003 2:02 PM > To:

Dear all, I have a problem where I must represent points with XYZ coordinates changing over time. I will do a number of operations on this data such as calculating the YZ-projection distance of the points to the origin over time, the frequency spectrum of the X-T data etc. I am trying to find a good way of representing this data with an appropriate data structure. It appears like

I have a number of x, y observations (Time, Conc) for a number of Subjects (with subject number Subj) and Doses. I can plot the individual points with xyplot fine: xyplot(Conc ~ Time | Subj, Groups=Dose, data=myData, panel = function(x,y) { panel.xyplot(x, y) panel.superpose(???) # Needs more here } ) I also like to plot on

Dear R-users Coming from a proc mixed (SAS) background I am trying to get into the use of (n)lme. In this connection, I have some (presumably stupid) questions which I am sure someone out there can answer: 1) With proc mixed it is easy to get a hold on the estimated variance parameters as they can be put out into a SAS data set. How do I do the same with lme-objects? For example, I can see the

Dear R users, I was wondering if anyone knows how to obtain(subset) the first and/or the last record of a subject in a longitudinal setup. Normally in SAS one uses first.variable1 and last.variable1. So my question is that is there an R way of doing this. Regards, -- Luwis Diya, Phd student (Biostatistics), Biostatistical Center, School Of Public Health, Catholic University of Leuven, U.Z. St

I wish to draw a graph representing multiple series (sets of x,y points). Each series has its own label and points within each series are joined by a line ordered by their X cooridnate. I would also like a legend automatically showing which each series is. Which high-level command can serve this purpose? I looked at my book but can't find such a command. Thanks! Mark

I'm fitting a lme growth curve model with two predictors and their interaction as predictors. The multilevel model is nested so that level 1 is time within the individual, and level 2 is the individual. I would like to plot the mean group-level trajectories at plus and minus 1 SD from the mean of the main effects composing the interaction term. Thus, the plot should have 4 lines (mean

Hi   I am using following code to produce a xyplot for some longitudinal data. There are 2 panels. It produced all longitudinal trajectories with mean profile. But since the dataset it very large plot looks very messy. I want to show, say 10 randomly selected individual longitudinal trajectories together with mean profile for entire dataset. Could any help me to alter the following code to do

Dear List: I have a data set with over 7000 students with about 4 observations over time per student. I want to examine the within-group fits of a random sample of this group as it takes forever to compute and draw all 7000 regressions. Here is the code I have used so far. >group<-groupedData(math~year|childid, data=scores) >group.list<-lmList(group)

dear helpers, I wonder if there is a way to read a molecular dynamic trajectory file ( binary file) produced by CHARMM into R. Something like that in matlab. Actually this will save tremendous effort in post processing. best regards karim

Hello, I'm attempting to create a smooth, 3D plot of a trajectory (rather than the cloud or wireframe functions). I would rather the individual data points not be visible. I've had no luck finding this on the graphics or help pages. Thank you in advance. Chris Some example data, just in case: 25 32 40 12 25 32 2 12 25 2 2 12 20 2 2 1 20 2 6 1 20 5 6 1 5 5 6

I'm looking at Pinheiro & Bates "Mixed-Effects Models in S and S-PLUS" at the moment. Several datasets are used, one of which is called "PBIB" (a partially balanced incomplete block design). All the other datasets can be found somewhere or other in R. However, I cannot locate PBIB, and it does not seem to be mentioned in the latest edition of the R Full Reference

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)

Hello, I'm developing an ordination using metaMDS (package vegan). The analysis identifies 3 distinct groups that I'd like to define by either adding circles or ellipses to help identify the groups. The data set is a spatial temporal data base depicting change in each of 4 areas over 3 time periods. I can add lines that would link each of the time - x - area trajectories, but

I wonder if someone can help me understand some counterintuitive simulation results. Below please find 12 lines of R code that theoretically, to the best of my understanding, should produce essentially a flat line with no discernable pattern. Instead, I see an initial dramatic drop followed by a slow rise to an asymptote. The simulation computes the mean of 20,000 simulated trajectories