Background: Incomplete information on death certificates makes recorded cause of death data less useful for public health monitoring and planning. Certifying physicians sometimes list only the mode of death (and in particular, list heart failure) without indicating the underlying disease(s) that gave rise to the death. This can prevent valid epidemiologic comparisons across countries and over time. Methods and Results: We propose that coarsened exact matching be used to infer the underlying causes of death where only the mode of death is known; we focus on the case of heart failure in U.S., Mexican and Brazilian death records. Redistribution algorithms derived using this method assign the largest proportion of heart failure deaths to ischemic heart disease in all three countries (53%, 26% and 22%), with larger proportions assigned to hypertensive heart disease and diabetes in Mexico and Brazil (16% and 23% vs. 7% for hypertensive heart disease and 13% and 9% vs. 6% for diabetes). Reassigning these heart failure deaths increases US ischemic heart disease mortality rates by 6%.Conclusions: The frequency with which physicians list heart failure in the causal chain for various underlying causes of death allows for inference about how physicians use heart failure on the death certificate in different settings. This easy-to-use method has the potential to reduce bias and increase comparability in cause-of-death data, thereby improving the public health utility of death records. Key Words: vital statistics, heart failure, population health, mortality, epidemiology
- Incumbency AdvantageProof that previously used estimators of electoral incumbency advantage were biased, and a new unbiased estimator. Also, the first systematic demonstration that constituency service by legislators increases the incumbency advantage.
- Mexican Health Care EvaluationAn evaluation of the Mexican Seguro Popular program (designed to extend health insurance and regular and preventive medical care, pharmaceuticals, and health facilities to 50 million uninsured Mexicans), one of the world's largest health policy reforms of the last two decades. Our evaluation features a new design for field experiments that is more robust to the political interventions and implementation errors that have ruined many similar previous efforts; new statistical methods that produce more reliable and efficient results using fewer resources, assumptions, and data; and an implementation of these methods in the largest randomized health policy experiment to date. (See the Harvard Gazette story on this project.)
- Presidency Research; Voting BehaviorResolution of the paradox of why polls are so variable over time during presidential campaigns even though the vote outcome is easily predictable before it starts. Also, a resolution of a key controversy over absentee ballots during the 2000 presidential election; and the methodology of small-n research on executives.
- Informatics and Data SharingReplication Standards New standards, protocols, and software for citing, sharing, analyzing, archiving, preserving, distributing, cataloging, translating, disseminating, naming, verifying, and replicating scholarly research data and analyses. Also includes proposals to improve the norms of data sharing and replication in science.
- International ConflictMethods for coding, analyzing, and forecasting international conflict and state failure. Evidence that the causes of conflict, theorized to be important but often found to be small or ephemeral, are indeed tiny for the vast majority of dyads, but are large, stable, and replicable wherever the ex ante probability of conflict is large.
- Legislative RedistrictingThe definition of partisan symmetry as a standard for fairness in redistricting; methods and software for measuring partisan bias and electoral responsiveness; discussion of U.S. Supreme Court rulings about this work. Evidence that U.S. redistricting reduces bias and increases responsiveness, and that the electoral college is fair; applications to legislatures, primaries, and multiparty systems.
- Mortality StudiesMethods for forecasting mortality rates (overall or for time series data cross-classified by age, sex, country, and cause); estimating mortality rates in areas without vital registration; measuring inequality in risk of death; applications to US mortality, the future of the Social Security, armed conflict, heart failure, and human security.
- Teaching and AdministrationPublications and other projects designed to improve teaching, learning, and university administration, as well as broader writings on the future of the social sciences.
- Incumbency Advantage
- Anchoring Vignettes (for interpersonal incomparability)Methods for interpersonal incomparability, when respondents (from different cultures, genders, countries, or ethnic groups) understand survey questions in different ways; for developing theoretical definitions of complicated concepts apparently definable only by example (i.e., "you know it when you see it").
- Automated Text AnalysisAutomated and computer-assisted methods of extracting, organizing, understanding, conceptualizing, and consuming knowledge from massive quantities of unstructured text.
- Causal InferenceMethods for detecting and reducing model dependence (i.e., when minor model changes produce substantively different inferences) in inferring causal effects and other counterfactuals. Matching methods; "politically robust" and cluster-randomized experimental designs; causal bias decompositions.
- Event Counts and DurationsStatistical models to explain or predict how many events occur for each fixed time period, or the time between events. An application to cabinet dissolution in parliamentary democracies which united two previously warring scholarly literature. Other applications to international relations and U.S. Supreme Court appointments.
- Ecological InferenceInferring individual behavior from group-level data: The first approach to incorporate both unit-level deterministic bounds and cross-unit statistical information, methods for 2x2 and larger tables, Bayesian model averaging, applications to elections, software.
- Missing Data & Measurement ErrorStatistical methods to accommodate missing information in data sets due to scattered unit nonresponse, missing variables, or values or variables measured with error. Easy-to-use algorithms and software for multiple imputation and multiple overimputation for surveys, time series, and time series cross-sectional data. Applications to electoral, and other compositional, data.
- Qualitative ResearchHow the same unified theory of inference underlies quantitative and qualitative research alike; scientific inference when quantification is difficult or impossible; research design; empirical research in legal scholarship.
- Rare EventsHow to save 99% of your data collection costs; bias corrections for logistic regression in estimating probabilities and causal effects in rare events data; estimating base probabilities or any quantity from case-control data; automated coding of events.
- Survey ResearchHow surveys work and a variety of methods to use with surveys. Surveys for estimating death rates, why election polls are so variable when the vote is so predictable, and health inequality.
- Anchoring Vignettes (for interpersonal incomparability)
- Systems and methods for calculating category proportions
- Method and Apparatus for Selecting Clusterings to Classify a Data Set
- Cross-Classroom and Cross-Institution Item Validation
- Participant Grouping for Enhanced Interactive Experience
- System for Estimating a Distribution of Message Content Categories in Source Data
- Method and Apparatus for Selecting Clusterings to Classify A Predetermined Data Set