Choice of stratification in Poisson process analysis of recurrent event data with environmental covariates
- 24 October 2002
- journal article
- Published by Wiley in Statistics in Medicine
- Vol. 21 (22) , 3383-3393
- https://doi.org/10.1002/sim.1279
Abstract
The Poisson process approach for studying the association between environmental covariates and recurrent events depends on the stratification of study period into intervals within which the baseline intensities are assumed constant. In this work we investigate the problem of bias and variance due to misspecification of this stratification. We suggest a cross‐validation approach to choosing a stratification model to balance the trade‐off between bias and variance. We also establish a connection between the Poisson process approach and case cross‐over studies. Copyright © 2002 John Wiley & Sons, Ltd.Keywords
This publication has 11 references indexed in Scilit:
- Bias in the case - crossover design: implications for studies of air pollutionEnvironmetrics, 2000
- Bidirectional Case-Crossover Designs for Exposures with Time TrendsPublished by JSTOR ,1998
- Control Sampling Strategies for Case-Crossover Studies: An Assessment of Relative EfficiencyAmerican Journal of Epidemiology, 1995
- Some Simple Robust Methods for the Analysis of Recurrent EventsTechnometrics, 1995
- On a likelihood-based approach in nonparametric smoothing and cross-validationStatistics & Probability Letters, 1995
- Some Graphical Displays and Marginal Regression Analyses for Recurrent Failure Times and Time Dependent CovariatesJournal of the American Statistical Association, 1993
- The Case-Crossover Design: A Method for Studying Transient Effects on the Risk of Acute EventsAmerican Journal of Epidemiology, 1991
- Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal DistributionsJournal of the American Statistical Association, 1989
- The Kernel Estimate of a Regression Function in Likelihood-Based ModelsJournal of the American Statistical Association, 1989
- On the regression analysis of multivariate failure time dataBiometrika, 1981