2 citations · 3 across the 6 of their papers we have counts for
6 papers
Pseudo-value Based Mean Cumulative Count Regression
Zachary R. McCaw, Alex Ocampo, Enrico Giudice +2
The mean cumulative function (MCF) summarizes how events accumulate over time for a recurrent or multi-component endpoint. The MCF, and its integral over a given time horizon, the…
Revealing the Truth: Calculating True Values in Causal Inference Simulation Studies via Gaussian Quadrature
Alex Ocampo, Enrico Giudice, Zachary R. McCaw +1
Simulation studies are used to understand the properties of statistical methods. A key luxury in many simulation studies is knowledge of the true value (i.e. the estimand) being ta…
Another look at statistical inference with machine learning-imputed data
Jessica Gronsbell, Jianhui Gao, Zachary R. McCaw +2
From structural biology to epidemiology, predictions from machine learning (ML) models increasingly complement costly gold-standard data, enabling faster, more affordable, and scal…
Simplifying Causal Mediation Analysis for Time-to-Event Outcomes using Pseudo-Values
Alex Ocampo, Enrico Giudice, Dieter A. Häring +3
Mediation analysis for survival outcomes is challenging. Most existing methods quantify the treatment effect using the hazard ratio (HR) and attempt to decompose the HR into the di…
What is Fair? Defining Fairness in Machine Learning for Health
Jianhui Gao, Benson Chou, Zachary R. McCaw +4
Ensuring that machine learning (ML) models are safe, effective, and equitable across all patients is critical for clinical decision-making and for preventing the amplification of e…
Exact Inference for Random Effects Meta-Analyses with Small, Sparse Data
Jessica Gronsbell, Zachary R McCaw, Timothy Regis +1
Meta-analysis aggregates information across related studies to provide more reliable statistical inference and has been a vital tool for assessing the safety and efficacy of many h…