Sharpening the Tools in the Shed: Improving Statistical Tools to Model Events

In this thesis, we aim to develop, implement and explain more novel and more complex analytical tools for time-to-event analysis and the number of events. Consecutively, we apply these models to topics and research questions in the field of management and vocational and organizational behavior. In particular, we introduce, develop and show the strenghts of (i) mixture cure model with correlated random effects, (ii) the use of multi-stage count regression models (including zero-inflated, two-part (hurdle) models and the k-finite mixture model of count regressions), and (iii) a multiple-membership survival model. More specifically, we aim to use these complex models to get improved insights in the time to find a job as well as early-career job attrition. We also use a novel methodology on the number of upward promotions of an employee using a two-stage promotion process.

Publication year:2020