https://konfound-project.github.io/ Recent content on KonFound-It! Hugo en Fri, 20 Dec 2024 00:00:00 +0000 https://konfound-project.github.io/post/2024-12-20-statistical-horizons-workshop/ Fri, 20 Dec 2024 00:00:00 +0000 https://konfound-project.github.io/post/2024-12-20-statistical-horizons-workshop/ Learn more and register: https://statisticalhorizons.com/seminars/sensitivity-analysis-causal-inference/ Explore the first hour of Kenneth Frank’s seminar on “Sensitivity Analysis for Causal Inference,” where he introduces key concepts and sets the foundation for exploring robust causal inference techniques. About this Seminar This seminar provides hands-on experience with two techniques for quantifying the sensitivity of causal inferences: Robustness of Inference to Replacement (RIR) and Impact Threshold for a Confounding Variable (ITCV). These techniques can be adapted to a range of analyses, including logistic regression, propensity-based approaches, and multilevel models. https://konfound-project.github.io/post/2023-08-13-faq/ Sun, 13 Aug 2023 00:00:00 +0000 https://konfound-project.github.io/post/2023-08-13-faq/ Introduction This document addresses some frequently asked questions regarding KonFound. Questions? Issues? Suggestions? Reach out through the KounFound-It! Google Group. See the appendices for background readings and software. For quick reference, visit: [Development version of the FAQ](https://www.dropbox.com/s/9eymdekym5g50o7/frequently asked questions for application of konfound-it.docx) Overview of all KonFound commands Main introductory slides for combined frameworks Background There are two basic frameworks for sensitivity analysis employed within KonFound. First is the Impact Threshold for a Confounding Variable (ITCV)—Frank (2000). https://konfound-project.github.io/post/2020-05-14-welcome/ Thu, 14 May 2020 00:00:00 +0000 https://konfound-project.github.io/post/2020-05-14-welcome/ Welcome to our space about sensitivity analysis. All of the assumptions of statistical analysis rarely hold. So the challenge for the pragmatist is to understand when evidence is strong enough to support action. That’s where sensitivity analysis comes in—so we can understand how robust our inferences are to challenges to our assumptions. One example is a statement such as: XX% of the estimated effect would have to be due to bias to change your inference about the effect. https://konfound-project.github.io/post/2020-05-12-why-robustness/ Tue, 12 May 2020 00:00:00 +0000 https://konfound-project.github.io/post/2020-05-12-why-robustness/ As those who work in public policy and health, we seek to help a broad range of people, with a broad range of statistical backgrounds, interpret uncertainty about public health findings regarding COVID-19. We observe that currently, there is little common language for expressing uncertainty. Consider Anthony Fauci’s quote (as in Healio on April 29): The trial, which began Feb. 21 this year, compared remdesivir with placebo in more than 1,000 patients. https://konfound-project.github.io/post/2020-05-01-presentation/ Fri, 01 May 2020 00:00:00 +0000 https://konfound-project.github.io/post/2020-05-01-presentation/ I summarized our current thinking on how robustness analysis can be applied to emerging COVID research in a brief presentation at an online conference entitled “COVID-19 and Public Policy and Management.” The conference was hosted by the Center on Technology, Data, and Society at Arizona State University, and a recording of the 15-minute talk, entitled “Communicating the Robustness of Inferences as COVID-19 Evidence Accumulates”, is available here. Communicating the Robustness of Inferences as COVID-19 Evidence Accumulates https://konfound-project.github.io/about/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/about/ All of the assumptions of statistical analysis rarely hold. The challenge for the pragmatist is understanding when evidence is strong enough to support action—and that is where sensitivity analysis comes in, allowing us to understand how robust our inferences are to challenges to our assumptions. Example Statement: XX% of the estimated effect would have to be due to bias to change your inference about the effect. Our work in the KonFound-It! https://konfound-project.github.io/page/faq/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/faq/ by Kenneth A. Frank, Qinyun Lin, Ran Xu, Spiro Maroulis, Guan Saw, & Josh Rosenberg Last updated: 7/5/2024 FAQ Dev Version Introduction This document addresses some frequently asked questions regarding KonFound. See the appendices for background readings and software. For quick reference, see: Overview of all KonFound commands Main introductory slides for combined frameworks Background There are two basic frameworks for sensitivity analysis employed within KonFound. First is the Impact Threshold for a Confounding Variable (ITCV)—Frank (2000). https://konfound-project.github.io/page/videos/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/videos/ Introduction to Sensitivity Analysis * KonFound-It! * September 2025 Introduction to Two Frameworks for Sensitivity Analysis * KonFound-It! * October 2025 Calculating Impact Threshold of a Confounding Variable (ITCV) in Stata * KonFound-It! * January 2026 Quantifying Sensitivity in Causal Inference with Kenneth Frank * Statistical Horizons * March 2025 Robustness of Inference to Replacement & Fragility for Logistic Regression and Hazard Functions * Michigan State University - Epidemiology & Biostatistics * April 2024 https://konfound-project.github.io/news/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/news/ Announcing Summer 2026 Workshop Posted: April 6, 2026 We are excited to announce our upcoming topical workshop at the ICPSR Summer Program in Quantitative Methods (July 13–17, 2026): Workshop Title: Sensitivity Analysis: Quantifying the Robustness of Inferences to Alternative Factors or Data Read More About Workshops → Summer 2025 Workshops & Conference Presentations Posted: April 7, 2025 Join the KonFound-It! team at several major conferences and training workshops throughout Summer 2025: https://konfound-project.github.io/page/guide/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/guide/ A Practical Guide to ITCV and RIRThe document is intended to serve as a practical guide to implementing the Impact Threshold of a Confounding Variable (ITCV), a sensitivity analysis approach based on omitted variables, and Robustness of Inference to Replacement (RIR), a sensitivity analysis approach based on replacement of cases. Download the Practical Guide (August 2025 version) → Citation *Frank, K. A., *Saw, G. K., Lin, Q., Xu, R., Rosenberg, J. https://konfound-project.github.io/page/publications/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/publications/ Featured Publications Practical Guide (2025) *Frank, K. A., *Saw, G. K., Lin, Q., Xu, R., Rosenberg, J. M., Maroulis, S. J., & Staudt Willet, K. B. (2025, August). A practical guide to impact threshold of a confounding variable (ITCV) and robustness of inference to replacement (RIR) (Version 2). Michigan State University. (* Co-first authors.) White paper. Web | PDF R Package (2024) Narvaiz, S., Lin, Q., Rosenberg, J. M., Frank, K. https://konfound-project.github.io/page/resources/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/resources/ Resource DirectoryAccess our suite of statistical packages, interactive web apps, explanatory slide decks, and core methodological publications. Quick Access Tools & Documentation Software & Web Apps R Package (CRAN Version) R Package (Development GitHub) KonFound-It! Shiny Web App Stata Package (SJ Article) WWC Sensitivity Benchmarks Guides & Slide Decks Frequently Asked Questions (FAQ) Overview of KonFound Techniques (PPTX) Overview of Commands & Inputs (DOCX) Quick Usage Examples Guide (PDF) Combined Frameworks Slides (PPTX) Framework Comparison Slides (PPTX) Publication Resources Empirical Examples & Calculators Published Empirical Application Examples (DOCX) — Real-world write-ups showing how to report KonFound results in peer-reviewed journals. https://konfound-project.github.io/page/talks/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/talks/ Talks & PresentationsExplore academic presentations, conference talks, and slide decks from the KonFound-It! research team. Upcoming Talks More Talks Coming Soon 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 https://konfound-project.github.io/page/case1-rir/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/case1-rir/ How believable are the effects of a growth mindset intervention? Background “A National Experiment Reveals Where a Growth Mindset Improves Achievement” (Yeager et al., 2019) Nature, Volume 573, pages 364–369 Abstract: A global priority for the behavioural sciences is to develop cost-effective, scalable interventions that could improve the academic outcomes of adolescents at a population level, but no such interventions have so far been evaluated in a population-generalizable sample. Here we show that a short (less than one hour), online growth mindset intervention—which teaches that intellectual abilities can be developed—improved grades among lower-achieving students and increased overall enrolment to advanced mathematics courses in a nationally representative sample of students in secondary education in the United States. https://konfound-project.github.io/page/case2-log/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/case2-log/ How convincing is the link between cohabitation and poverty? Background “Marriage, Work, and Racial Inequalities in Poverty: Evidence from the U.S” (Thiede et al., 2017) Journal of Marriage and Family, Volume 79, pages 1241–1257 Abstract: This paper explores recent racial and ethnic inequalities in poverty, estimating the share of racial poverty differentials that can be explained by variation in family structure and workforce participation. The authors use logistic regression to estimate the association between poverty and race, family structure, and workforce participation. https://konfound-project.github.io/page/case3-itcv/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/case3-itcv/ How robust is the link between a recent eviction and material hardship? Background “Eviction’s Fallout: Housing, Hardship, and Health” (Desmond & Kimbro, 2015) Social Forces, Volume 94, pages 295-324 Abstract: Millions of families across the United States are evicted each year. Yet, we know next to nothing about the impact eviction has on their lives. Focusing on low-income urban mothers, a population at high risk of eviction, this study is among the first to examine rigorously the consequences of involuntary displacement from housing. https://konfound-project.github.io/page/case4-cop/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/case4-cop/ How robust is the link between low birthweight and childhood IQ when accounting for unobserved selection? Background “Unobservable Selection and Coefficient Stability: Theory and Evidence” (Oster, 2019) Journal of Business & Economic Statistics, Volume 37, Issue 2, pages 187-204 Abstract: A common approach to evaluating robustness to omitted variable bias is to observe coefficient movements after inclusion of controls. This is informative only if selection on observables is informative about selection on unobservables. https://konfound-project.github.io/page/workshops/ Mon, 01 Jan 0001 00:00:00 +0000 https://konfound-project.github.io/page/workshops/ Workshops & TrainingLearn how to apply sensitivity analysis techniques (RIR, ITCV, COP) in R, Stata, and the KonFound-It! web app. Upcoming Workshops More Workshops Coming Soon We regularly host training sessions at major academic conferences and methodology institutes. Check back soon for new dates, or browse our past sessions below for course materials and slide decks. Featured Recent Workshops ICPSR Summer Program in Quantitative Methods Dates: July 13–17, 2026 (10:00 AM – 3:00 PM ET) | Format: Virtual