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Activity Number: 239 - Study Design and Analysis for Complex Survival Data
Type: Contributed
Date/Time: Monday, July 29, 2019 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #307241
Title: Estimating Menarcheal Age Distribution from Partially Recalled Data
Author(s): Sedigheh Mirzaei Salehabadi* and Debasis Sengupta and Rahul Ghosal
Companies: St. Jude Children's Research Hospital and Indian Statistical Institute and North Carolina State University
Keywords: Interval censoring; Informative censoring; Retrospective study; Maximum likelihood estimator; Current status data; Self consistency

In a cross-sectional study, pubertal females were asked to recall the time of menarche, if experienced. Some respondents recalled the date exactly,some recalled only the month or the year of the event, and some were unable to recall anything. We consider estimation of the menarcheal age distribution from this interval censored data. A complicated interplay between age-at-event and calendar time, together with the evident fact of memory fading with time, makes the censoring informative. We propose a model where the probabilities of various types of recall would depend on the time since menarche, through a multinomial regression function. Establishing consistency and asymptotic normality of the parametric MLE requires a bit of tweaking of the standard asymptotic theory, as the data format varies from case to case. We also provide a non-parametric MLE, propose a computationally simpler approximation, and establish the consistency of both of these estimators under mild conditions. We study the small sample performance of the parametric and non-parametric estimators through Monte Carlo simulations. Graphical check of the assumption of the multinomial model and data analysis are provided

Authors who are presenting talks have a * after their name.

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