DSAS - MSc Public Lecture - Jiaqi Mu

Title: EXPLORING THE ESTIMABILITY OF MARK-RECAPTURE MODELS WITH INDIVIDUAL, TIME-VARYING COVARIATES USING THE SCALED LOGIT LINK FUNCTION.

Abstract: 

Mark-recapture studies are often used to estimate the survival of individuals in a population and identify factors that affect survival in order to understand how the population might be affected by changing conditions. Factors that vary between individuals and over time, like body mass, present a challenge because they can only be observed when an individual is captured. Several models have been proposed to deal with the missing-covariate problem and commonly impose a logit link function which implies that the survival probability varies between 0 and 1. In

this thesis, I explore the estimability of four possible models when survival is linked to the covariate through a scaled logit link function which imposes some upper limit, c < 1. Through a combination of theoretical analysis and simulation, I show that the binomial model is not estimable under the scaled link while the other three models remain estimable.

Supervisor: Dr. Simon Bonner