A novel method for lifecourse modelling with time-varying covariates

Solomon Beer, University of Galway

Co-authors: Erin Dunn, Purdue University; Sherief Eldeeb, Massachusetts General Hospital; Andrew Simpkin, University of Galway; Andrew Smith, University of the West of England

Abstract: Prospective cohort studies collect many repeated measures, including exposures, outcomes and covariates, over time. Where an exposure is collected repeatedly, interest often lies in determining whether timing has a differential effect on a later outcome. However, few studies consider the effect of time-varying covariates which may impact associations. We present an extension to the Structured Life Course Modelling Approach (SLCMA) which allows for the adjustment of time-varying covariates.