R code for implementation of methods referred to in the manuscript entitled "Dynamic prediction of survival in cystic fibrosis: A landmarking analysis using patient registry data"
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
README.md
baseline_cumulative_hazards.RData
baseline_cumulative_hazards.csv
estimated_survival_probabilities.Rmd
estimated_survival_probabilities.pdf
log_hazard_ratios.RData
log_hazard_ratios.csv
mixed_models_outofsample_prediction.Rmd
mixed_models_outofsample_prediction.pdf
mixoutsamp_v2.R
times.RData
times.csv

README.md

This repository provides R code for implementation of methods referred to in the following paper:

"Dynamic prediction of survival in cystic fibrosis: A landmarking analysis using UK patient registry data" Ruth Keogh, Shaun Seaman, Jessica Barrett, David Taylor-Robinson, Rhonda Szczesniak. Epidemiology 2018. In Press.

mixoutsamp_v2.R: R code for obtaining out-of-sample predictions from a mixed model fitted using lme.

mixed_models_outofsample_prediction: Illustrating the use of mixoutsamp on a freely-available exmple data set. Rmd file and corresponding pdf file.

estimated_survival_probabilities: R code for obtaining estimated survival probabilities using the dynamic prediction model developed in the above manuscript. Rmd file and corresponding pdf file.

baseline_cumulative_hazards, times, log_hazard_ratios: csv and RData files containing estimated baseline cumulative hzards, event/censoring time and log hazard ratios from the dynamic prediction model developed in the above manuscript. These are used to obtain the estimated survival probabilities.