CCI News
Explore advancements in causal inference methods shaping precision medicine and interdisciplinary research at the Center for Causal Inference (CCI).
Award
Dr. Nandita Mitra Wins 2024 Cupples Award for Excellence in Research, Teaching, and Leadership
May 9, 2024
Nandita Mitra, PhD, Professor of Biostatistics, has been awarded the 2024 L. Adrienne Cupples Award for her outstanding contributions to research, teaching, and leadership in biostatistics and public health.
Award
Bryan Blette and Andrew Ying Win ASA Paper Award
January 20, 2022
We are pleased to announce that Bryan Blette and Andrew Ying were seclected as the winners of the highly competitive ASA Biometrics Section Paper award. The awardes will present their […]
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New Working Paper on Nonparametric Instrumental Variable Estimators
October 17, 2021
Doubly robust nonparametric instrumental variable estimators for survival outcomes Youjin Lee, Edward H Kennedy, Nandita Mitra Instrumental variable (IV) methods allow us the opportunity to address unmeasured confounding in causal […]
Award
Jason Roy, PhD, Selected for 2021 ASA Causality in Statistics Education Award
June 4, 2021
We are pleased to announce that Jason Roy, CCI Co-Director, has been selected for the 2021 ASA Causality in Statistics Education Award for his work to advance Causality in Statistics […]
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New Working Paper on Job Vacancies and Immigration
December 10, 2020
Job Vacancies and Immigration: Evidence from the Mariel Supply Shock L. Jason Anastasopoulos, George J. Borjas, Gavin G. Cook, and Michael Lachanski We use the Conference Board’s Help-Wanted Index (HWI) […]
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New Working Paper on Unmeasured Confounding and Time
November 10, 2020
Controlling for Unmeasured Confounding in the Presence of Time: Instrumental Variable for Trend Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy, Dylan S. Small Unmeasured confounding is a key threat […]
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New Working Paper on Bayesian Nonparametric Cost-Effectiveness Analyses
September 8, 2020
Bayesian Nonparametric Cost-Effectiveness Analyses: Causal Estimation and Adaptive Subgroup Discovery Arman Oganisian, Nandita Mitra, Jason Roy Cost-effectiveness analyses (CEAs) are at the center of health economic decision making. While these […]
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Discussion on the Evaluation of Mobile Health Interventions
September 1, 2020
Moving Toward Rigorous Evaluation of Mobile Health Interventions Kristin A. Linn Qian, Klasnja and Murphy provide an assumption that allows for unbiased estimation of treatment effects in microrandomized trials when […]
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New Working Paper on a non‐parametric projection‐based estimator for the probability of causation
January 23, 2020
A non‐parametric projection‐based estimator for the probability of causation, with application to water sanitation in Kenya Maria Cuellar and Edward H. Kennedy Current estimation methods for the probability of causation […]
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New working paper on causal inference with zero-inflated outcomes
March 2, 2019
A Bayesian Nonparametric Model for Zero-Inflated Outcomes: Prediction, Clustering, and Causal Estimation Arman Oganisian, Nandita Mitra, and Jason Roy Researchers are often interested in predicting outcomes, conducting clustering analysis to […]
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New working paper on longitudinal mediation
March 1, 2019
Bayesian Longitudinal Causal Inference in the Analysis of the Public Health Impact of Pollutant Emissions Chanmin Kim, Corwin M Zigler, Michael J Daniels, Christine Choirat, and Jason A Roy Pollutant […]
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New working paper on differences-in-differences
February 28, 2019
Patterns of Effects and Sensitivity Analysis for Differences-in-Differences Luke J. Keele, Dylan S. Small, Jesse Y. Hsu, and Colin B. Fogarty Applied analysts often use the differences-in-differences (DID) method to […]
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New paper on continuous instrumental variables
February 27, 2019
Robust causal inference with continuous instruments using the local instrumental variable curve Edward H. Kennedy, Scott Lorch, and Dylan S. Small Instrumental variables are commonly used to estimate effects of […]
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New paper on instrumental variables estimation
August 15, 2018
Bounded, efficient and multiply robust estimation of average treatment effects using instrumental variables Wang L, Tchetgen Tchetgen E. Instrumental variables (IVs) are widely used for estimating causal effects in the […]
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New paper on cost and cost effectiveness with measured and unmeasured confounders
June 1, 2018
Estimating cost-effectiveness from claims and registry data with measured and unmeasured confounders Elizabeth Handorf, Daniel Heitjan, Justin Bekelman, Nandita Mitra Link The analysis of observational data to determine the cost-effectiveness […]
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New paper on treatment effects with multiple outcomes
June 1, 2018
Estimating scaled treatment effects with multiple outcomes Edward H Kennedy, Shreya Kangovi, Nandita Mitra Link In classical study designs, the aim is often to learn about the effects of a […]
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New paper on eliminating survivor bias in IV
May 29, 2018
Eliminating survivor bias in two-stage instrumental variable estimators. Vansteelandt S, Walter S, Tchetgen Tchetgen E. Link Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis […]
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New paper on sensitivity analysis and power for IV
May 29, 2018
Sensitivity analysis and power for instrumental variable studies Wang X, Jiang Y, Zhang NR, Small DS. Link In observational studies to estimate treatment effects, unmeasured confounding is often a concern. […]
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New paper on 2-stage instrumental variables estimation
March 26, 2018
A general approach to evaluating the bias of 2‐stage instrumental variable estimators Fei Wan, Dylan Small, and Nandita Mitra Unmeasured confounding is a common concern when researchers attempt to estimate […]
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New paper on causal inference with missing covariates
March 26, 2018
Bayesian nonparametric generative models for causal inference with missing at random covariates Jason Roy, Kirsten J. Lum, Bret Zeldow , Jordan D. Dworkin, Vincent Lo Re III, and Michael J. […]
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New Publication on Doubly Robust Methods for Cost Effectiveness Estimation
April 2, 2017
A doubly robust approach for cost–effectiveness estimation from observational data Li, Vachani, Epstein, Mitra Estimation of common cost–effectiveness measures, including the incremental cost–effectiveness ratio and the net monetary benefit, is […]
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New Working Paper on Effect Modification
February 7, 2017
A new, powerful approach to the study of effect modification in observational studies Kwonsang Lee, Dylan S. Small, Paul R. Rosenbaum Effect modification occurs when the magnitude or stability of […]
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New Publication on Trend-in-Trend Design
October 20, 2016
The Trend-in-Trend Research Design for Causal Inference. Ji X, Small DS, Leonard CE, Hennessy S. Cohort studies can be biased by unmeasured confounding. We propose a hybrid ecologic-epidemiologic design called […]
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New Publication on Second Control Groups
October 18, 2016
Constructed Second Control Groups and Attenuation of Unmeasured Biases Samuel D. Pimentel, Dylan S. Small & Paul R. Rosenbaum The informal folklore of observational studies claims that if an irrelevant […]
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New Publication on Sensitivity Analysis
October 4, 2016
An adaptive Mantel-Haenszel test for sensitivity analysis in observational studies. Rosenbaum PR, Small DS In a sensitivity analysis in an observational study with a binary outcome, is it better to […]
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New Publication on Causal Mediation
August 1, 2016
A framework for Bayesian nonparametric inference for causal effects of mediation. Kim C, Daniels MJ, Marcus BH, Roy JA We propose a Bayesian non-parametric (BNP) framework for estimating causal effects […]
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New Publication on Bayesian Marginal Structural Models
June 26, 2016
A Bayesian nonparametric approach to marginal structural models for point treatments and a continuous or survival outcome. Roy J, Lum KJ, Daniels MJ. Marginal structural models (MSMs) are a general […]
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New Publication on Instrumental Variable Methods
May 1, 2016
Selection Bias When Using Instrumental Variable Methods to Compare Two Treatments But More Than Two Treatments Are Available. Ertefaie A, Small D, Flory J, Hennessy S. Instrumental variable (IV) methods […]
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New Publication on Propensity Scores
April 19, 2016
An evaluation of bias in propensity score-adjusted non-linear regression models Fei Wan, Nandita Mitra Propensity score methods are commonly used to adjust for observed confounding when estimating the conditional treatment […]