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20242026
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stat.ME2026

Doubly Robust Estimators of Quantile Treatment Effects With Semiparametric Cumulative Probability Models

Hao Wu, Chun Li, Bryan E. Shepherd

The causal inference literature has traditionally focused on estimating the mean of the potential outcome, whereas evaluating how a treatment affects the entire outcome distributio…

stat.ME2025

Estimating treatment effects with a unified semi-parametric difference-in-differences approach

Julia C. Thome, Andrew J. Spieker, Peter F. Rebeiro +3

Difference-in-differences (DID) approaches are widely used for estimating causal effects with observational data before and after an intervention. DID traditionally estimates the a…

stat.ME2025

Unified and Simple Sample Size Calculations for Individual or Cluster Randomized Trials with Skewed or Ordinal Outcomes

Shengxin Tu, Chun Li, Caroline De Schacht +4

Sample size calculations can be challenging with skewed continuous outcomes in randomized controlled trials (RCTs). Standard t-test-based calculations may require data transformati…

stat.ME2024

Probability-scale residuals for event-time data

Eric S. Kawaguchi, Bryan E. Shepherd, Chun Li

The probability-scale residual (PSR) is defined as , where is the observed outcome and is a random variable from the fitted distribution. The PSR is pa…

stat.ME2024

Between- and Within-Cluster Spearman Rank Correlations

Shengxin Tu, Chun Li, Bryan E. Shepherd

Clustered data are common in practice. Clustering arises when subjects are measured repeatedly, or subjects are nested in groups (e.g., households, schools). It is often of interes…