17. Time-Varying Confounding: Some Practical Considerations in a Likelihood Framework

  1. Carlo Berzuini,
  2. Philip Dawid and
  3. Luisa Bernardinelli
  1. Rhian Daniel,
  2. Bianca De Stavola and
  3. Simon Cousens

Published Online: 25 JUN 2012

DOI: 10.1002/9781119945710.ch17

Causality: Statistical Perspectives and Applications

Causality: Statistical Perspectives and Applications

How to Cite

Daniel, R., De Stavola, B. and Cousens, S. (2012) Time-Varying Confounding: Some Practical Considerations in a Likelihood Framework, in Causality: Statistical Perspectives and Applications (eds C. Berzuini, P. Dawid and L. Bernardinelli), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781119945710.ch17

Editor Information

  1. Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Cambridge, UK

Author Information

  1. Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, UK

Publication History

  1. Published Online: 25 JUN 2012
  2. Published Print: 13 JUL 2012

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780470665565

Online ISBN: 9781119945710

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Keywords:

  • time-varying confounding, in a likelihood framework;
  • longitudinal studies, time-to-event and losses to follow-up;
  • causal inferences, using Monte Carlo simulation;
  • competing events and challenges, unbalanced measurement times;
  • assumed causal structure for observed data, and DAG;
  • conditional exchangeability assumption;
  • time-to-event outcomes, in longitudinal studies;
  • conditional exchangeability states, conditionally independent of outcomes;
  • g-computation formula, and parametric modelling choices;
  • Nelson-Aalen cumulative hazard estimates

Summary

This chapter contains sections titled:

  • Introduction

  • General setting

  • Identifying assumptions

  • G-computation formula

  • Implementation by Monte Carlo simulation

  • Analyses of simulated data

  • Further considerations

  • Summary

  • References