similar to: Longitudinal study with three treatments

Hello R user, I have a data set from a longitudinal study ( sample below) where subjects are followed over time. Second column (status) contains info about if subject is dead or still in the study and third column is time measured in the week. Here is what I need: if status is not dead or unknown take the last week, if status is dead or unknown I need to have corresponding week. Desired resulst:

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

Hi all, I asked this before the holiday, didn't get any response. So would like to resend the message, hope to get any fresh attention. Since this is not purely lme technical question, so I also cc-ed R general mailing list, hope to get some suggestions from there as well. I asked some questions on how to analyze longitudinal study with only 2 time points (baseline and a follow-up)

Dear list, I have been struggling with this for some time now, and for the last hour I have been struggling to make a working example for the list. I hope someone out there have some experience with plotting longitudinal data that they will share. My data is some patient data with three different time stamps. First the patients are identified at different times (first time stamp). Second, they

Dear All, I would like to find something ( references, code,..) to implement a comparison of three treatments in an observational study using the 'Propensity Score'. Any help is much appreciated. Thanks! Giovanni -- dr. Giovanni Parrinello Department of Biotecnologies Medical Statistics Unit University of Brescia Viale Europa, 11 25123 Brescia email: parrinel at med.unibs.it Phone:

Hi In R,how to do sample size calculation for three-way incomplete block crossover study where within subject residual standard deviation,treatment difference and power is given. Thanks in advance. Regards Jose [[alternative HTML version deleted]]

Hi all, I a semi-beginner with R and I am working with the plm package to examine a longitudinal dataset. Each individual in this dataset has a longitudinal weight for the probability that he or she remains in the sample. Unfortunately, I have not found an argument to use weights in the plm function? I tried ?weights=? like in standard lm or in nlme or lm4 but it does not work. I asked the

Hi all: I have a question about the sample size calculation. It's a pilot study,which includes 2 groups(low,high),3 time point(3,6,9 monthes).Each person has 3 results which according to the 3 time points.So it's a longitudinal study. I want to calculate the minimum sample size from the pilot study, but can't find the solution since the data is highly skewed and it's a

Dear R-Users! Is there a possibility in R to do analyze longitudinal survey data (repeated measures in a survey)? I know that for longitudinal data I can use lme() to incorporate the correlation structure within individual and I know that there is the package survey for analyzing survey data. How can I combine both? I am trying to calculate design-based estimates. However, if I use svyglm() from

i am studying Longitudinal Data Analysis and want to carry it with R.anyone knows any materials about Longitudinal Data Analysis with R in the internet which i can download? thank you.

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

Dear R people, I have a matrix like this: var1 var2 var3 var4 a1 7.1 7.2 8.1 8.2 a2 10.5 10.6 ... ... a3 b1 b2 b3 b4 c1 c2 ... The matrix row names are "a1", "a2", ...... and the matrix column names are "var1", "var2", "var3" and "var4". Now I want to reshape this data into a

Hi, Can one tell me which procedure will fit an ordinal logistic regression model for longitudinal data set. To be precise, I have both dichotomous and polytomous items. Also, I would like to specify different covariance structures (unstructured, ar1 etc) for trial runs. Thanks -- View this message in context:

Dear R-users, I would like to announce the release of the new package JMbayes available from CRAN (http://CRAN.R-project.org/package=JMbayes). This package fits shared parameter models for the joint modeling of normal longitudinal responses and event times under a Bayesian approach using JAGS, WinBUGS or OpenBUGS. The package has a single model-fitting function called jointModelBayes(),

Dear R-users, I would like to announce the release of the new package JMbayes available from CRAN (http://CRAN.R-project.org/package=JMbayes). This package fits shared parameter models for the joint modeling of normal longitudinal responses and event times under a Bayesian approach using JAGS, WinBUGS or OpenBUGS. The package has a single model-fitting function called jointModelBayes(),

I used gam for data analysis a lot. Is it possible to use gam to analyze longitudinal data? I mean, besides the working independence assumption, can i specify other more reasonable covariance structure in gam? [[alternative HTML version deleted]]

Hello all, I am working on a longitudinal study of children in the UK and trying the PAN package for imputation of missing data, since it fulfils the critical criteria of taking into account individual subject trend over time as well as population trend over time. In order to validate the procedure I have started by deleting some known values ?we have 6 annual measures of height on 300 children

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

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.

Dear R-help mailing list,   I have this problem, I have a joint  longitudinal and survival data of the form say   ID Time Failuretime Censoringind longitudinalmeasure 1  0     35                  0                123 1  10    35                 0                 120  1   25   35                 1                   123 2   0    23                  0                   100 2   10  23