caa a22 4500 605476187 CHVBK 20210128100355.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s10985-015-9333-0 doi (NATIONALLICENCE)springer-10.1007/s10985-015-9333-0 The current duration design for estimating the time to pregnancy distribution: a nonparametric Bayesian perspective [Elektronische Daten] [Dario Gasbarra, Elja Arjas, Aki Vehtari, Rémy Slama, Niels Keiding] This paper was inspired by the studies of Niels Keiding and co-authors on estimating the waiting time-to-pregnancy (TTP) distribution, and in particular on using the current duration design in that context. In this design, a cross-sectional sample of women is collected from those who are currently attempting to become pregnant, and then by recording from each the time she has been attempting. Our aim here is to study the identifiability and the estimation of the waiting time distribution on the basis of current duration data. The main difficulty in this stems from the fact that very short waiting times are only rarely selected into the sample of current durations, and this renders their estimation unstable. We introduce here a Bayesian method for this estimation problem, prove its asymptotic consistency, and compare the method to some variants of the non-parametric maximum likelihood estimators, which have been used previously in this context. The properties of the Bayesian estimation method are studied also empirically, using both simulated data and TTP data on current durations collected by Slama et al. (Hum Reprod 27(5):1489-1498, 2012). Springer Science+Business Media New York, 2015 McMC nationallicence Posterior consistency nationallicence Data augmentation nationallicence Logistic process prior nationallicence Generalized gamma convolution process nationallicence Gasbarra Dario Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland aut Arjas Elja Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland aut Vehtari Aki Department of Computer Science, Aalto University, Espoo, Finland aut Slama Rémy French Institute of Health and Medical Research, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Inserm-Univ. Grenoble Alpes, Grenoble, France aut Keiding Niels Department of Public Health, University of Copenhagen, Copenhagen, Denmark aut Lifetime Data Analysis Springer US; http://www.springer-ny.com 21/4(2015-10-01), 594-625 1380-7870 21:4<594 2015 21 10985 https://doi.org/10.1007/s10985-015-9333-0 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10985-015-9333-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Gasbarra Dario Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland aut NATIONALLICENCE 700 1- Arjas Elja Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland aut NATIONALLICENCE 700 1- Vehtari Aki Department of Computer Science, Aalto University, Espoo, Finland aut NATIONALLICENCE 700 1- Slama Rémy French Institute of Health and Medical Research, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Inserm-Univ. Grenoble Alpes, Grenoble, France aut NATIONALLICENCE 700 1- Keiding Niels Department of Public Health, University of Copenhagen, Copenhagen, Denmark aut NATIONALLICENCE 773 0- Lifetime Data Analysis Springer US; http://www.springer-ny.com 21/4(2015-10-01), 594-625 1380-7870 21:4<594 2015 21 10985