Ph.D., 2001, Free University of Amsterdam, The Netherlands

Dr. Judith Lok's research program currently focuses on statistical methods in HIV-AIDS related problems, using observational data. Together with Dr. James Robins and Dr. Miguel Hernan she is working on estimating the optimal start of HAART treatment in HIV positive patients. The main issue there is that patients who are treated and patients who are not treated are not comparable. Together with Dr. Ron Bosch and Dr. Michael Hughes she is working on the course of CD4 after treatment in the long run (7-8 years), using the ALLRT data. The main issue there is that not all patients who started treatment also entered into ALLRT, leading to considerable dropout. Together with Dr. Victor DeGruttola she is working on estimating the effect of HAART as a function of time since infection. Also there, the main issue is that patients who are treated and patients who are not treated are not comparable.

Judith Lok developed an intellectual and mathematical framework for Structural Nested Models, both for continuous time measurements and for discrete time measurements. In collaboration with Dr. Richard Gill, Dr. Aad van der Vaart and Dr. James Robins, she provided a rigorous proof of the asymptotic properties, consistency and asymptotic normality, of the resulting estimators in discrete time, which was published in Statistica Neerlandica. She has also provided the first proofs of these asymptotic properties in continuous time. This work has recently been published in the Scandinavian Journal of Statistics, "Structural nested models and standard software: a mathematical foundation through partial likelihood" and is upcoming in the Annals of Statisics, "Statistical modelling of causal effects in continuous time". These methods have been applied to estimate treatment effects in HIV infected subjects. Judith Lok is still working on structural nested models in continuous time.

Research areas: causality, counterfactuals, longitudinal data, observational studies, competing risks, HIV.