This thesis develops statistical methodology for causal inference based on observational longitudinal data. The work is motivated by problems in pharmacoepidemiology, where hazard ratios routinely are used to assess the association of time-fixed and time-dependent exposure with time-to-event outcomes. However, the interpretation of hazard ratios as the measure of treatment effect is hampered for many reasons. Causal effect parameters may instead be formulated as intervention-specific mean outcomes, for instance to target the effect of dynamic treatment regimes on the absolute risk scale.
Targeted minimum loss-based estimation (TMLE) provides a general template for efficient estimation of such causal parameters in semiparametric models. The main part of my thesis is concerned with a generalization of the TMLE template to a continuous-time setting. In this setting, the number and schedule of covariate changes and intervention time-points are allowed to be subject-specific and to occur in continuous time. I propose a novel targeting estimation algorithm, where nuisance parameters are handled by super learning, and derive the asymptotic distribution of the resulting estimator.
In my thesis I also suggest extensions of generalized random forests for conditional and marginal causal effect estimation with time-to-event outcome observed in presence of right-censoring and competing risks. I apply these methods to Danish registry data to search through all drugs on the market for repurposing effects.
Associate Professor Andreas Kryger Jensen, Section of Biostatistics, Department of Public Health, University of Copenhagen
Assistant Professor Edward H. Kennedy, Department of Statistics & Data Science, Carnegie Mellon University
Professor Søren Feodor Nielsen, Center for Statistics, Department of Finance, Copenhagen Business School
You can find CSS next to the Botanical Garden, 5 minutes from Nørreport station.
Meeting room 5.2.46 is the library of the Biostatistics section, located in building 5, 2nd floor, room 46. See the map below for directions inside CSS.