similar to: Testing significance of interaction between group and longitudinal change for part of the age range in a mixed linear model

R-helpers: In the construction of control charts for statistical quality control objectives, one might choose to estimate the control limits for the mean using the mean range of the samples. This requires multiplying the mean range by a correction factor, often called "d2", that is tabulated in many books. The origin of "d2" seems to be table 2 of the following paper:

Dear all, I'm attempting to use a piecewise regression to model the trajectory of reproductive traits with age in a longitudinal data set using a mixed model framework. The aim is to find three slopes and two points- the slope from low performance in early age to a point of high performance in middle age, the slope (may be 0) of the plateau from the start of high performance to the

Hi all, I need a little help for construct an state's map on R. The first problem is to get the data. I have a datafile of longitude and latitude in the follow format: trajectory latitude longtude T -22.045618 -51.287056 T -22.067078 -51.265888 T -22.067039 -51.207249 T -22.059690 -48.089695 T -22.075529 -48.074608 T -22.072460 -48.044472 T -22.062767 -48.298473 T -22.077349

R-Helpers: I would like to perform sample size calculations for an experiment. As part of this process, I would like to know how various assumptions affect the sample size calculation. For instance, one thing that I would like to know is how the calculated sample size changes as I vary the difference that I would like to detect. I tried the following first, but got the associated error

Hi Is there any way to fit a bivaraite longitudinal mixed model using R. I have a data set with col names resp1 (Y_ij1), resp2 (Y_ij2), timepts (t_ij), unit(i) j=1,2,..,m and i=1,2,..n. I want to fit the following two models Model 1 Y_ij1, Y_ij2 | U_i = u_i ~ N(alpha + u_i + beta1*t_ij, Sigma) U_i ~ iid N(0, sigu^2) Sigma = bivariate AR structure alpha and beta are vectors of order 2.

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation

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

Dear R List, I am trying to use mixed models to analyze an intervention and want to make sure I am doing it correctly. The intervention is for lowing cholesterol and there are two groups: one with an intervention and one without. The subjects were evaluated a differing amount of time, so there were between 2 and 7 visits, equally spaced. Sample output is below. TC is total cholesterol,

R Experts: I am conducting a meta-analysis where the effect measures to be pooled are simple proportions. For example, consider this data from Fleiss/Levin/Paik's Statistical methods for rates and proportions (2003, p189) on smokers: Study N Event P(Event) 1 86 83 0.965 2 93 90 0.968 3 136 129 0.949 4 82 70 0.854 Total

Hi everyone, I?m trying to do a spaghetti plot and I know I?m doing all wrong, It must be. What I need: 15 subjects, each with measurements over 5 different times (t1, ..., t5), and the variable that I need to represent in the spaguetti plot is given by: PCR = b0 + b1 * ti + epsilon B0, - baseline of each subject B1 - trajectory of each subject over time (so multiply by t) Epsilon - error

Greetings, I have the following problem: I want to compare a "parameter trajectory", i.e. a series of real numbers (representing equidistant samples of a time-varying parameter) produced by some "model", to a reference trajectory, measured from the real world, in order to get a rating of how good the model that produced the first trajectory is. Ok, so I use the RMS of the

Hi all, I am trying to plot the fitted trajectories for each individual from an individual growth model (fit with a linear mixed effects model in lme). How can I plot each person's trajectory in the *same* panel, along with the mean-level trajectory? Below is an image of a plot similar to what I'm trying to create (from: http://jpepsy.oxfordjournals.org/content/31/10/1002/F6.large.jpg):

I am trying to simulate the trajectory of the pension assets of one person. In C-like syntax, it looks like this: daily.wage.growth = 1.001 # deterministic contribution.rate = 0.08 # deterministic 8% Wage = 10 # initial Asset = 0 # initial for (10,000 days) { Asset += contribution.rate * Wage

Hi, I'm trying to read some trajectory files (text files) which have the form: # trial n # t X Y 0 1 2 0.2 1 3 0.4 1.2 4 ... # trial n+1 # t X Y 0 1 2 0.2 1.3 3.3 0.4 1.5 5 ... ... where the symbol # means that the line is not a numeric value, but I still need to read the number of the trial (n=1, 2, etc.). I

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

Hello, Does anyone know how to make "movies" in R by making a sequence of plots? I'd like to animate a long trajectory for exploratory purposes only, without creating a bunch of image files and then using another program to string them together. In Splus I would do this using double.buffer() to eliminate the flickering caused by replotting. For instance, with a 2-D trajectory

Hi Rosa, You pass a vector to ggplot, which expects a data.frame. I am sure you meant to do this: point7$y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7 $epsilon_7 ggplot(point7, aes(time, y_point7)) + geom_line() HTH Ulrik On Wed, 19 Jul 2017 at 20:37 Rosa Oliveira <rosita21 at gmail.com> wrote: > Hi everyone, > > I?m trying to do a spaghetti plot and I

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')