2025/09/03 by Angela Carollo, Hein Putter, Paul H.C. Eilers +1 · 1 voice
Decision Sciences · Social Sciences · Economics, Econometrics and Finance · #demographic modeling and climate adaptation #Insurance, Mortality, Demography, Risk Management #Spatial and Panel Data Analysis
paper · doi:10.1177/00491241251374193
openalex publication_date 2025/09/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
Models for time-to-event data are based on transition rates between states, and to define such hazards of experiencing an event, the time scale over which the process evolves needs to be identified. In many applications, however, more than one time scale might be of importance. Here, we demonstrate how to model a hazard jointly over two time dimensions. The model assumes a smooth bivariate hazard function, and the function is estimated by two-dimensional <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mi>P</mml:mi> </mml:math> -splines. We provide an R package for the analysis of event history data with two time scales. As an example, we model transitions from cohabitation to marriage or separation simultaneously over the age of the individual and the duration of the cohabitation. We use data from the German Family Panel (pairfam) and demonstrate that considering the two time scales as equally important provides additional insights about the transition from cohabitation to marriage or separation.