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Hi, I'm reading van Belle et al "Biostatistics" and trying to run a cox test using a dataset from: http://faculty.washington.edu/~heagerty/Books/Biostatistics/chapter16.html (Primary Biliary Cirrhosis data link at top of the page), I'm using the following code: --------------- start of code library(survival) liver <-

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

Hey all, In order to test if a marker is a risk factor, I built two models (using cox proportional hazard model). One model included this marker, and the other is not. Then, I use R package risksetROC to test how much predictive value did the marker add to this model. I get two C statistics by analyzing the linear predictors of the two models into this package. The qustion is How to test if two

Hi, I'm trying to figure out if there are any packages allowing one to fit mixed models (or non-linear mixed models) to data that includes censoring. I've done some searching already on CRAN and through the mailing list archives, but haven't discovered anything. Since I may well have done a poor job searching I thought I'd ask here prior to giving up. I understand that

Dear useRs, here is the announcement for the next "new" package: sandwich 0.1-3. sandwich provides heteroskedasticity (and autocorrelation) consistent covariance matrix estimators (also called HC and HAC estimators). The former are implemented in the function vcovHC() (which was available in strucchange before - and independently in hccm() in John Fox's car package). And the

Dear useRs, here is the announcement for the next "new" package: sandwich 0.1-3. sandwich provides heteroskedasticity (and autocorrelation) consistent covariance matrix estimators (also called HC and HAC estimators). The former are implemented in the function vcovHC() (which was available in strucchange before - and independently in hccm() in John Fox's car package). And the

I want to run a GEE for a time series of counts. The data are daily respiratory mortality counts and so there aren't any 'clusters' in the longitudinal sense. Neither the gee or geese packages work. The gee one wont run at all and the geese one produces NaNs or just runs indefinitely depending on how long the time series is. Any ideas how to make these work of any other packages that

In case more of you come across my request from this morning, I've already gotten several great tips, which I summarize here since one or two of these did not come across R-help as well. A team of fellow political scientists is on this problem like "white-on-rice"! Brandt, Patrick, John T. Williams Benjamin O. Fordham, and Brian Pollins. 2000. "Dynamic Modeling for Persistent

hi all- I am doing some research, have never used R before until today and need to understand the following program for a project. if some one could PLEASE help me understand this program ASAP i would GREATLY appreciate it (any syntax/ statistic comments would be great) PLEASE PLEASE HELP!! THANKYOU!!! -on a side note, it seems to me that R doesnt include the pv, and it was calculated

Dear all, I am interested to evaluate reclassification using net reclassification improvement and Integrated Discrimination Index IDI after survival analysis (Cox proportional hazards using stcox). I search a R package or a R code that specifically addresses the categorical NRI for time-to-event data in the presence of censored observation and, if possible, at different follow-up time points. I