Event dependent sampling of recurrent events

The effect of event-dependent sampling of processes consisting of recurrent events is investigated when analyzing whether the risk of recurrence increases with event count. We study the situation where processes are selected for study if an event occurs in a certain selection interval. Motivation comes from psychiatric epidemiology where repeated hospital admissions are studied for patients with affective disease, as seen in Kessing et al. (Acta Psychiatr Scand 109:339–344, 2004b). For the selected processes, either only disease course from selection and onwards is used in the analysis, or, both retrospective and prospective disease course histories are used. We examine two methods to correct for the selection depending on which data are used in the analysis. In the first case, the conditional distribution of the process given the pre-selection history is determined. In the second case, an inverse-probability-of-selection weighting scheme is suggested. The ability of the methods to correct for the bias due to selection is investigated with simulations. Furthermore, the methods are applied to affective disease data from a register-based study (Kessing et al. Br J Psychiatry 185:372–377, 2004a) and from a long-term clinical study (Kessing et al. Acta Psychiatr Scand 109:339–344, 2004b).

[1]  R. Post,et al.  Transduction of psychosocial stress into the neurobiology of recurrent affective disorder. , 1992, The American journal of psychiatry.

[2]  Lars Vedel Kessing,et al.  Non-parametric estimation and model checking procedures for marginal gap time distributions for recurrent events. , 2007, Statistics in medicine.

[3]  P. Andersen,et al.  Course of illness in depressive and bipolar disorders , 2004, British Journal of Psychiatry.

[4]  Chiung-Yu Huang,et al.  Nonparametric estimation of the bivariate recurrence time distribution. , 2005, Biometrics.

[5]  Philip Hougaard,et al.  Analysis of Multivariate Survival Data , 2001 .

[6]  Thorkild I. A. Sørensen,et al.  Inference Methods for Correlated Left Truncated Lifetimes: Parent and Offspring Relations in an Adoption Study , 2006, Lifetime data analysis.

[7]  S. Keleş,et al.  Recurrent events analysis in the presence of time‐dependent covariates and dependent censoring , 2004 .

[8]  P. Andersen,et al.  The predictive effect of episodes on the risk of recurrence in depressive and bipolar disorders – a life‐long perspective , 2004, Acta psychiatrica Scandinavica.

[9]  E. W. Olsen,et al.  Recurrence in affective disorder: analyses with frailty models. , 1999, American journal of epidemiology.

[10]  J. Robins,et al.  Semiparametric regression estimation in the presence of dependent censoring , 1995 .

[11]  Niels Keiding,et al.  Statistical Models Based on Counting Processes , 1993 .

[12]  Heping Zhang,et al.  Recurrence of bipolar disorders and major depression , 2003, European archives of psychiatry and clinical neuroscience.

[13]  Richard D. Gill,et al.  A counting process approach to maximum likelihood estimation in frailty models , 1992 .

[14]  E. Parner,et al.  Correcting for selection using frailty models , 2006, Statistics in medicine.

[15]  Jerald F. Lawless,et al.  Inference Based on Retrospective Ascertainment: An Analysis of the Data on Transfusion-Related AIDS , 1989 .

[16]  Niels Keiding,et al.  Design and analysis of time-to-pregnancy , 2006, Statistical methods in medical research.

[17]  J F Lawless,et al.  State duration models in clinical and observational studies. , 1999, Statistics in medicine.

[18]  J. Robins,et al.  Recovery of Information and Adjustment for Dependent Censoring Using Surrogate Markers , 1992 .