ruthkeogh
Professor of Biostatistics & Epidemiology, Department of Medical Statistics at the London School of Hygiene & Tropical Medicine. UKRI Future Leaders Fellow.
London School of Hygiene & Tropical Medicine
Pinned Repositories
BARS
causal_sim
Simulating longitudinal data from marginal structural models using the additive hazards model. https://arxiv.org/abs/2002.03678
CF-transplant.github.io
CF_patient_forecast
The changing demography of the cystic fibrosis population: Forecasting future numbers of adults in the UK
ISCB_Causal_Survival
landmark_CF
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". https://journals.lww.com/epidem/Fulltext/2019/01000/Dynamic_Prediction_of_Survival_in_Cystic_Fibrosis_.5.aspx
meas_error_handbook
Ruth H Keogh & Jonathan W Bartlett. Measurement error as a missing data problem. In: Handbook of Measurement Error and Variable Selection. 2019. To appear. https://arxiv.org/abs/1910.06443
MI-CC
Multiple imputation (MI) for case-cohort and nested case-control studies. https://onlinelibrary.wiley.com/doi/full/10.1111/biom.12910
MI-TVE
Multiple imputation in Cox regression when there are time-varying effects of covariates. https://onlinelibrary.wiley.com/doi/full/10.1002/sim.7842
sequential_trials
R code for implementation of the simulation study described in the paper: "Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models"
ruthkeogh's Repositories
ruthkeogh/sequential_trials
R code for implementation of the simulation study described in the paper: "Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models"
ruthkeogh/causal_sim
Simulating longitudinal data from marginal structural models using the additive hazards model. https://arxiv.org/abs/2002.03678
ruthkeogh/MI-CC
Multiple imputation (MI) for case-cohort and nested case-control studies. https://onlinelibrary.wiley.com/doi/full/10.1111/biom.12910
ruthkeogh/MI-TVE
Multiple imputation in Cox regression when there are time-varying effects of covariates. https://onlinelibrary.wiley.com/doi/full/10.1002/sim.7842
ruthkeogh/landmark_CF
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". https://journals.lww.com/epidem/Fulltext/2019/01000/Dynamic_Prediction_of_Survival_in_Cystic_Fibrosis_.5.aspx
ruthkeogh/meas_error_handbook
Ruth H Keogh & Jonathan W Bartlett. Measurement error as a missing data problem. In: Handbook of Measurement Error and Variable Selection. 2019. To appear. https://arxiv.org/abs/1910.06443
ruthkeogh/BARS
ruthkeogh/CF-transplant.github.io
ruthkeogh/CF_patient_forecast
The changing demography of the cystic fibrosis population: Forecasting future numbers of adults in the UK
ruthkeogh/ISCB_Causal_Survival
ruthkeogh/lengthofstay
ruthkeogh/supersampling