similar to: Announce: Summer Program in Data Analysis (SPIDA) 2012

Longitudinal and Multilevel Data in R and Stan ICPSR short course: May 28 to June 1, 2018 May 28: Introduction to R by John Fox May 29 to June 1: Longitudinal and Multilevel Data in R and Stan by Georges Monette Sponsored and organized by ICPSR, University of Michigan and held at York University in Toronto, Ontario Course description:https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0226

DATIC (www.datic.uconn.edu<http://www.datic.uconn.edu>) is offering 4 workshops at the University of Connecticut in June, 2018: Mixture Modeling, Introduction to Data Analysis in R, Multilevel Modeling in R, and Dyadic Analysis with R. Registration is now open. Go to www.datic.uconn.edu<http://www.datic.uconn.edu> for more information and to register for the workshops. Mixture

[Env: Win XP] I've just upgraded from R 2.12.2 to R 2.13.1. As part of my upgrade process, I typically install some in-development packages from R-Forge that are not on cran. But for the first time, it doesn't work. e.g., > install.packages("p3d", repos="http://R-Forge.R-project.org") trying URL

I am using a multilevel modeling approach to model change in a person's symptom score over time (i.e., longitudinal individual growth models). I have been using the lme function in the multilevel package for the analyses, but my problem is that my outcome (symptoms) and one of my predictors (events) are count data, and are non-normal. Do you have any suggestions for how to deal with them?

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

I am trying to plot an interaction in a multilevel model. Here is some sample data. In the following example, it is longitudinal (i.e., repeated measures), so the outcome, score (at each of the three time points), is nested within the individual. I am interested in the interaction between gender and happiness predicting score. id <- c(1,1,1,2,2,2,3,3,3) age <-

When I set up my debian linux (unstable) system, the only R debian packages were on CRAN, so I followed directions and added the last line to my /etc/apt/sources.list euclid: # m /etc/apt/sources.list deb http://debian.yorku.ca/debian/ unstable main non-free contrib deb http://debian.yorku.ca/debian/non-US unstable/non-US main contrib non-free deb http://hexamon.ccs.yorku.ca/ unixteam-debs/

[Running debian stable] I followed the instructions at http://cran.r-project.org/bin/linux/debian, adding deb http://cran.R-project.org/bin/linux/debian lenny-cran/ to /etc/apt/sources.list. But apt-get still leaves me with R 2.7.1. How can I diagnose what's wrong or correct this? euclid: /etc/apt # apt-get update Hit http://debian.yorku.ca stable Release.gpg Ign http://debian.yorku.ca

Hi, does anyone out there have a recommendation for multilevel / random effects and longitudinal analysis? My dream book would be something that's both accessible to a non-statistician but rigorous (because I seem to be slowly turning into a statistician) and ideally would use R. Peter

I recently was forced to do a dist-upgrade and rebuild my kernel, so a lot has changed on my system, and I don't know if that is related to the errors & warnings I get from apt-get update. Any ideas? thanks -Michael euclid:~# apt-get update Get: 1 http://debian.yorku.ca stable Release.gpg [378B] Get: 2 http://debian.yorku.ca stable/updates Release.gpg [189B] Get: 3

On 9/30/2020 7:23 PM, Jason Keltz wrote: > On 9/30/2020 4:11 PM, Remy Zandwijk via samba wrote: > >>> On 30 Sep 2020, at 21:42, Jason Keltz via samba >>> <samba at lists.samba.org> wrote: >>> >>> >>> On 9/30/2020 3:01 PM, Remy Zandwijk via samba wrote: >>>>>>> On the client, add: >>>>>>>

R Users, The d/p/q/r functions for the bridge distribution are now available in bridgedist. When a random intercept follows the bridge distribution, as detailed in Wang and Louis (2003) <doi:10.1093/biomet/90.4.765 <http://dx.doi.org/10.1093/biomet/90.4.765>>, a marginalized random-intercept logistic regression will still be a logistic regression with marginal coefficients that are

Hello everyone, I am employing the waba method from the multilevel package for obtaining a within-group correlation (Description: http://bg9.imslab.co.jp/Rhelp/R-2.4.0/src/library/multilevel/man/waba.html). Does anybody know a way or a calculation for obtaining a significance value for that correlation? And another question: Does anybody know whether it is possible to save individual

Hello, I am a Second year PhD student in Dept of Management and Organization from NUS Business School, Singapore. Presently I am doing a multilevel analysis for a small research project with my supervisor. While surfing the web, I found your website on multilevel analysis. These are very useful for the understanding of the concept to me. I was also trying to learn more by completing the lab

Hi, I'm trying to reshape my data set from wide to tall format for multilevel modeling. Unfortunately, the function I typically use (make.univ from the multilevel package) does not appear to work with unbalanced data frames, which is what I'm dealing with. Below is an example of the columns of a data frame similar to what I'm working with: ID a1 a2 a4 b2 b3 b4 b5 b6 Below

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've split it into three patches now and also made it fit to current CVS, with, I believe, Karl's changes for the double free bug. Order for the patches is: icecast-multilevel-fallback.patch icecast-timewindow.patch icecast-yp-override.patch As for docs: How? What format? Any specific layout? Melanie -------------- next part -------------- A non-text attachment was scrubbed...

Perhaps I am not looking in the right place, but I am looking for a way to use lmer() to run a multilevel model that incorporates sampling weights. I have used the Lumley survey package to use sampling weights in the past, but according to post I found online from Thomas Lumley in mid-2012, R is currently not equipped to be able to do this. His post is here:

I have two series of events over time and I want to construct a graph of the relative frequency/density of these events that allows their distributions to be sensibly compared. The events are the milestones items in my project on milestones in the history of data visualization [1], and I want to compare trends in Europe vs. North America. I decided to use a graph of two overlaid density

Hi List, I have the following problem: I am using the multilevel package and make.univ function for available in the package and then xyplot from lattice and I want to know how could I be able to use the ?coefficient? for the straight line that passes the data ? Example from help: library(multilevel) data(univbct) #a data set already in univariate or stacked form for job satisfaction