240214 William Ruth
Statistical Considerations in Multilevel Mediation Analysis.

Speaker: William Ruth, University of Montreal

Date and Time: Wednesday, February 14, 2024 - 2:00pm to 3:00pm


Causal mediation analysis is a popular tool for studying complicated causal dependence between multiple variables. The main question we want to answer is to what extent the effect of an exposure, X, on a response, Y, is mediated by a third variable, M. One common approach involves fitting some regression models and computing simple, albeit non-linear, functions of the estimated coefficients. Uncertainty quantification for these "mediation effects" is non-trivial in even the simplest settings, with published simulation studies finding that asymptotic standard errors obtained from the delta method often perform poorly in finite samples. A popular alternative to these analytical standard error formulas is to use the bootstrap, a computational tool which involves using repeated draws from an approximate sampling distribution to assess the standard error of a statistic. We present a range of implementations for the bootstrap on a complicated statistical model involving non-linearity and mixed-effects, and illustrate our analysis on a dataset investigating the relationship between trustworthiness of peoples' preferred news source and willingness to adhere to pandemic lockdown mandates.

Networks »Networks
MfPH – Training »MfPH – Training
2023-2024 MfPH Next Generation Seminar Series »2023-2024 MfPH Next Generation Seminar Series
240214 William Ruth
Université de Montréal »Université de Montréal
Nonpharmaceutical Interventions (NPIs) »Nonpharmaceutical Interventions (NPIs)
Covid-19 »Covid-19
Social networks »Social networks
Mathematical modelling of human response behaviour during pandemics »Mathematical modelling of human response behaviour during pandemics
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