= Germán Rodríguez
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<Germán Rodríguez> works on statistical methods for population research. His Princeton teaching and research site connects <generalized linear models>, <survival analysis> and demographic questions about event timing. The site's biographical note identifies his training in <biostatistics> and his work in population research.https://grodri.github.io/[Author's biography and research statement]{ref}
His <Survival Models by Germán Rodríguez> explains how <survival functions> and <hazard functions> encode the same event-time distribution in different ways. With <right censoring>, an event observed at $t$ contributes density $f(t)$, whereas an observation ending without an event contributes $S(t)$. Writing the contribution as $S(t)h(t)^\delta$, with event indicator $\delta\in\{0,1\}$, makes that distinction explicit. These likelihood conventions let incomplete follow-up inform estimation without treating a censored time as an observed failure.<Survival Models by Germán Rodríguez>[Sections 7.1–7.2, equation 7.7]{ref}
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