similar to: Longitudinal Factor Analysis

Good Morning, I am trying to create a new column of character strings based on the first two letters in a string in another column. I believe that I need to use some combination of ifelse and grep but I am not totally sure how to combine them. I am not totally sure why the command below isn't working. Obviously it isn't finding anything that matches my criteria but I am not sure why. Any

This question teeters on the brink of general statistics rather than an R-specific issue, but I'm hoping it boils down to how I coded V&R's EM algorithm for finite mixture modeling and not something worse (i.e. that my plan is impossible). Briefly, I'm trying to simulate an experiment where the hypothesis concerns bimodal vs. unimodal distributions, in order to see what

Hi, I want to fit 3 beta distributions to my data which ranges between 0 and 1. What are the functions that I can easily call and specify that 3 beta distributions should be fitted? I have already looked at normalmixEM and fitdistr but they dont seem to be applicable (normalmixEM is only for fitting normal dist and fitdistr will only fit 1 distribution, not 3). Is that right? Also, my data has 26

Sat, 19 Jul 2014 15:03:03 -0400 I am not sure exactly where the problem is here. I am using a sieve script that sorts various incoming messages into their own mailbox. MS Outlook does not show those folders if they are not directly under INBOX. EXAMPLE: drwx------ 31 vmail vmail 1.0K 2014-07-19 14:46:55 EDT ./ drwx------ 3 vmail vmail 512B 2014-07-02 13:52:03 EDT ../ drwx------ 5

Hi all- So sorry to bother you all with something pretty basic. I am trying to add the lines method output from svysmooth to a svyplot with style="grayhex". However, the line either appears in the wrong place or if I am running in R Studio it causes the system to crash. I know this is something to do with Lattice graphics, but for the life of me I can not figure out how. Dr. Lumley

Hi - I am trying to find and describe missing data in a time series. For instance, in the library openair, there is a data frame called "mydata": library(openair) head(mydata) date ws wd nox no2 o3 pm10 so2 co pm25 1 1998-01-01 00:00:00 0.60 280 285 39 1 29 4.7225 3.3725 NA 2 1998-01-01 01:00:00 2.16 230 NA NA NA 37 NA NA NA 3 1998-01-01 02:00:00

Happy Friday fellow R users. I need some help - I am trying to make a graph using ggplot 2 of some lead isotope ratios. Normally, the isotope mass number appears as a superscript before the chemical symbol. However, I cannot figure out how to do this ggplot2's axis labels. The closest I have come is using "." In front of the numbers I am superscripting e.g: ggplot(....

Hello - So I am trying to use ggplot2 to show a linear regression between two variables, but I want to also show the fit of the line on the graph as well. I am using ggplot2 for other graphics in what I am working on, so even though this would be a fairly easy thing to do in Excel, I would prefer to do it in R to keep my look and feel, and I think ggplot2 is just cooler. Here is a sample

Greetings - I am working on some data that contain chemical names with air concentrations, and I am creating a data frame with date/time and each chemical having its own column. However, these are organic chemicals (e.g. 1-butene, 2,3,4-trimethylbenzene etc). The package I am going to be using the data with is openair, and many of the great functions require you to specify a column name which

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]]

Hi all, does anybody know about R implementations for quantile regression for longitudinal data? I am just aware of a very basic version of R. Koenker's approach using fixed effects. Thanks in advance Armin

Dear Dimitris, I have exactly the same problem than you, Do you get some solution? Thanks, Lola Lola Gadea Profesora titular de Economía Aplicada/Lecturer in Applied Economics Universidad de Zaragoza/University of Zaragoza (Spain) lgadea@unizar.es <http://estructuraehistoria.unizar.es/personal/lgadea/index.html>http://estructuraehistoria.unizar.es/personal/lgadea/index.html Grupo de

Hi R-masters! I trying model Heart disease mortality in my country with a lme model like this: m1.lme<-lme(log(rdeath)~age*year,random=~age|year,data=dados) where: rdeath is rate of mortality per 100000 person per age and year age: age of death (22 27 32 37 42 47 52 57 62 67 72 77 82) year: year of death (1980:2002) I don?t have problem to fit the model, but in

 I would like to use GLM to analysis  a longitudinal data  any one know which library in R do so thanks alot [[alternative HTML version deleted]]

Hi there, I have a dataset from a longitudinal study with a lot of drop-out. I want to implement the inverse probability weighting method by Robins 1995 JASA paper "Analysis of semiparametric regression models for repeated outcomes in the presence of missing data". Does anyone know if there is a package to do it in R (or other software)? Thanks a lot! Lei

Hi, I am trying to model a score over time. This score shows a ceiling effect. I was willing to use a longitudinal tobit model, such as the one described by Twisk et al. (Twisk_Longitudinal tobit regression: A new approach to analyze outcome variables with floor or ceiling effects_JCE_2009) but it is programmed for STATA. Has anyone used such models in R? Any other idea? David Biau.

Hi, Can anyone recommend one or more good sample datasets for multivariate longitudinal data? (eg. a dataset containing a mixture of continuous, categorical and date/time variables) I'm looking for something which I can use for testing and examples for my ggplot graphics package. A selection of datasets which use different date time classes would also be useful, although I could probably

Hi Group, Create some example data. set.seed(1) wide_data <- data.frame( id=c(1:10), predictor1 = sample(c("a","b"),10,replace=TRUE), predictor2 = sample(c("a","b"),10,replace=TRUE), predictor3 = sample(c("a","b"),10,replace=TRUE), measurement1=rnorm(10), measurement2=rnorm(10)) head(wide_data) id

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

Hi, Can anyone tell me if they know of any functions written for regression trees with a longitudinal dataset. I've got tree, rpart and maptree, but these all seem to be for univariate responses. Thanks for your time, Cath -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send