TY - JOUR

T1 - Retrospective ascertainment of recurrent events

T2 - An application to time to pregnancy

AU - Scheike, TH

AU - Petersen, JH

AU - Martinussen, T

PY - 1999/9

Y1 - 1999/9

N2 - Retrospectively ascertained data are common in many areas, including demography, epidemiology, and actuarial science. The main objective of this article is to study the effect of retrospective ascertainment on inference regarding recurrent events of time to pregnancy (TTP) data. For the particular TTP dataset that we consider, couples are included retrospectively based on their first pregnancy and then followed prospectively to a second pregnancy or to end of study. We consider a conditional model for the recurrent events data where the second TTP is included only if it is observed and a full model where the nonobserved second TTPs are included as suitably right censored. We furthermore consider two different approaches to modeling the dependencies of the recurrent events. A traditional frailty model, where the frailty enters the model as an unobserved covariate, and a marginal frailty model are applied. We find that efficiency is gained from including the second TTPs, with the full model being the most efficient. Further, the marginal frailty model is preferred over the traditional frailty model because estimates of covariate effects are easier to interpret and are ore robust to changes in the frailty distribution.

AB - Retrospectively ascertained data are common in many areas, including demography, epidemiology, and actuarial science. The main objective of this article is to study the effect of retrospective ascertainment on inference regarding recurrent events of time to pregnancy (TTP) data. For the particular TTP dataset that we consider, couples are included retrospectively based on their first pregnancy and then followed prospectively to a second pregnancy or to end of study. We consider a conditional model for the recurrent events data where the second TTP is included only if it is observed and a full model where the nonobserved second TTPs are included as suitably right censored. We furthermore consider two different approaches to modeling the dependencies of the recurrent events. A traditional frailty model, where the frailty enters the model as an unobserved covariate, and a marginal frailty model are applied. We find that efficiency is gained from including the second TTPs, with the full model being the most efficient. Further, the marginal frailty model is preferred over the traditional frailty model because estimates of covariate effects are easier to interpret and are ore robust to changes in the frailty distribution.

KW - censoring

KW - Cox regression

KW - discrete survival data

KW - fecundity

KW - frailty model

KW - left truncation

KW - random effects

KW - right truncation

KW - right censoring

KW - time to pregnancy

KW - TRUNCATED SURVIVAL-DATA

KW - REGRESSION-MODELS

KW - AIDS

KW - HETEROGENEITY

KW - DISTRIBUTIONS

U2 - 10.2307/2669984

DO - 10.2307/2669984

M3 - Journal article

VL - 94

SP - 713

EP - 725

JO - Journal of the American Statistical Association

JF - Journal of the American Statistical Association

SN - 0162-1459

IS - 447

ER -