Retrospective ascertainment of recurrent events: An application to time to pregnancy
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Retrospective ascertainment of recurrent events : An application to time to pregnancy. / Scheike, TH; Petersen, JH; Martinussen, T.
In: Journal of the American Statistical Association, Vol. 94, No. 447, 09.1999, p. 713-725.Research output: Contribution to journal › Journal article › Research › peer-review
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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 -
ID: 320880595