10 papers
Unifying Statistical and Mathematical Modeling Through a Causal Inference Lens
Paul N Zivich
Within the biological, physical, and social sciences, there are two broad quantitative traditions: statistical and mathematical modeling. Both traditions have the common pursuit of…
A Law of Iterated Expectation Primer for Causal Inference
Ashley I. Naimi, Razieh Nabi, Lindsay J. Collin +2
The g-formula is a foundational tool for identifying causal effects in observational data. This tool is based on the law of iterated expectation, a key mathematical identity in sta…
Estimating equations for causal survival analysis with pooled logistic regression
Paul N Zivich, Stephen R Cole, Bonnie E Shook-Sa +2
Background: Pooled logistic regression models are commonly applied in survival analysis. However, the standard implementation can be computationally demanding, which is further exa…
Novel g-computation algorithms for time-varying actions with recurrent and semi-competing events
Alena Sorensen D'Alessio, Lucas M. Neuroth, Jessie K Edwards +2
Background: A core aspect of epidemiology is determining the impacts of potential public health interventions over time. With long follow-up periods, epidemiologists may need to co…
Structural Nested Mean Models Under Parallel Trends with Interference
Zach Shahn, Paul Zivich, Audrey Renson
Despite the common occurrence of interference in Difference-in-Differences (DiD) applications, standard DiD methods rely on an assumption that interference is absent, and comparati…
Code Sharing in Healthcare Research: A Practical Guide and Recommendations for Good Practice
Lukas Hughes-Noehrer, Matthew J Parkes, Andrew Stewart +8
As computational analysis becomes increasingly more complex in health research, transparent sharing of analytical code is vital for reproducibility and trust. This practical guide,…