Nonparametric double additive cure survival models: An application to the estimation of the non-linear effect of age at first parenthood on fertility progression

Author:

Bremhorst Vincent1,Kreyenfeld Michaela2,Lambert Philippe13

Affiliation:

1. Université catholique de Louvain, Institut de Statistique, Biostatistique et Sciences Actuarielles, Louvain-la-Neuve, Belgium.

2. Hertie School of Governance, Berlin, Germany.

3. Université de Liège, Faculté des sciences sociales, Méthodes quantitatives en sciences sociales, Liège, Belgium.

Abstract

This article introduces double additive models to describe the effect of continuous covariates in cure survival models, thereby relaxing the traditional linearity assumption in the two regression parts. This class of models extends the classical event history models when an unknown proportion of the population under study will never experience the event of interest. They are used on data from the German Socio-Economic Panel (GSOEP) to examine how age at first birth relates to the timing and quantum of fertility for given education levels of the respondents. It is shown that the conditional probability of having further children decreases with the mother's age at first birth. While the effect of age at first birth in the third birth's probability model is fairly linear, this is not the case for the second child with an accelerating decline detected for women that had their first kid beyond age 30.

Publisher

SAGE Publications

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

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1. The Deep Promotion Time Cure Model;IEEE Transactions on Neural Networks and Learning Systems;2024

2. Transitions to Second Birth and Birth Intervals in France and Spain: Time Squeeze or Social Norms?;Comparative Population Studies;2023-07-11

3. Comments on: Nonparametric estimation in mixture cure models with covariates;TEST;2023-05-17

4. Air Pollution Impairs Subjective Happiness by Damaging Their Health;International Journal of Environmental Research and Public Health;2021-09-30

5. Inclusion of time‐varying covariates in cure survival models with an application in fertility studies;Journal of the Royal Statistical Society: Series A (Statistics in Society);2019-08-25

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