Talks & Presentations
Explore academic presentations, conference talks, and slide decks from the KonFound-It! research team.Upcoming Talks
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Check back soon for upcoming conference presentations and invited academic seminars.
Recent Presentations
Quantifying Sensitivity to Selection on Unobserved Covariates: Recasting the Coefficient of Proportionality
Joint Statistical Meetings (JSM 2025) — Multi-faceted Approaches to Sensitivity Analysis for Observational Studies
Date: August 6, 2025 (10:30 AM – 12:30 PM CT) | Location: Nashville, TN
- Presenters: Kenneth A. Frank, Qinyun Lin, & Spiro Maroulis
- Abstract: Perhaps the most prevalent index used for sensitivity analyses is Oster’s (2019) Coefficient of Proportionality (COP). In this paper, we reconceptualize the COP as a function of unobserved covariates’ correlations with the focal predictor and outcome. Our correlation-based approach addresses recent critiques of Oster’s COP while preserving the comparison of selection on unobserved covariates to selection on observed covariates without depending on an analyst’s subjective choice of baseline model covariates.
Multi-faceted Approaches to Sensitivity Analysis
Society for Causal Inference (SCI 2025)
Date: May 16, 2025 (10:15–11:45 AM ET)
Location: Detroit, MI
Refining Oster’s Coefficient of Proportionality
Joint Statistical Meetings (JSM 2024)
Date: August 4, 2024 (8:30–9:30 PM PT)
Location: Pacific Time / Virtual
Fragility for Logistic Regression & Cox Models
University of Gothenburg — School of Public Health
Date: May 23, 2024 (1:00–2:45 PM CET) | Gothenburg, Sweden
Robustness of Inference to Replacement in Biostatistics
Michigan State University — Department of Biostatistics
Date: April 11, 2024 (3:30–4:30 PM ET) | Fee Hall, MSU
Sensitivity Analysis for Pragmatic Social Science
Emory University — Workshop on Advanced Research Methods (WARM)
Date: March 21, 2024 (8:30–9:30 PM ET) | Virtual
Communicating the Robustness of COVID-19 Studies
AERA Virtual Research Learning Series
Date: May 1, 2020
Watch Dr. Ken Frank discuss methods for communicating sensitivity analyses and statistical robustness during public health crises.
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