Explanipedia

aamatch: Artless Automatic Multivariate Matching for Observational Studies Open

Paul R. Rosenbaum · 2025

alcoholSurv: Light Daily Alcohol and Longevity Open

Paul R. Rosenbaum · 2025

An Introduction to the Theory of Observational Studies Open

Paul R. Rosenbaum · 2025

Assessing the Ambulatory Surgery Center Volume-Outcome Association Open

Siddharth Jain, Paul R. Rosenbaum, Joseph G. Reiter, Omar I. Ramadan, Alexander S. Hill , et al. · 2024

Importance In surgical patients, it is well known that higher hospital procedure volume is associated with better outcomes. To our knowledge, this volume-outcome association has not been studied in ambulatory surgery centers (ASCs) in the …

Mortality Among Older Medical Patients at Flagship Hospitals and Their Affiliates Open

Siddharth Jain, Paul R. Rosenbaum, Joseph G. Reiter, Omar I. Ramadan, Alex S. Hill , et al. · 2023

A Second Evidence Factor for a Second Control Group Open

Paul R. Rosenbaum · 2023

In an observational study of the effects caused by a treatment, a second control group is used in an effort to detect bias from unmeasured covariates, and the investigator is content if no evidence of bias is found. This strategy is not en…

Explaining racial disparities in surgical survival: a tapered match analysis of patient and hospital factors Open

Karen B. Lasater, Paul R. Rosenbaum, Linda H. Aiken, J. Margo Brooks-Carthon, Rachel R. Kelz , et al. · 2023

Objectives Evaluate whether hospital factors, including nurse resources, explain racial differences in Medicare black and white patient surgical outcomes and whether disparities changed over time. Design Retrospective tapered-match. Settin…

Observational (Non-Randomized) Studies Open

Paul R. Rosenbaum · 2023

In 1965, the statistician William G. Cochran defined an observational study as an attempt to draw inferences about the effects caused by a treatment, a policy, a program, an exposure, or an intervention in a context in which randomized exp…

Redefining Multimorbidity in Older Surgical Patients Open

Omar I. Ramadan, Paul R. Rosenbaum, Joseph G. Reiter, Siddharth Jain, Alex S. Hill , et al. · 2023

BACKGROUND: Multimorbidity in surgery is common and associated with worse postoperative outcomes. However, conventional multimorbidity definitions (≥2 comorbidities) label the vast majority of older patients as multimorbid, limiting clinic…

Bahadur Efficiency of Observational Block Designs Open

Paul R. Rosenbaum · 2023

To be convincing, an observational or nonrandomized study of causal effects must demonstrate that its conclusions cannot be readily explained by a small unmeasured bias in the way individuals were assigned to treatment or control. The Baha…

Defining Multimorbidity in Older Patients Hospitalized with Medical Conditions Open

Siddharth Jain, Paul R. Rosenbaum, Joseph G. Reiter, Omar I. Ramadan, Alex S. Hill , et al. · 2022

Involvement of multinational corporations in social innovation: Exploring an emerging phenomenon Open

Christine Holmström Lind, Olivia Kang, Anna Ljung, Paul R. Rosenbaum · 2022

Risk of Parkinson's disease after anaesthesia and surgery Open

Siddharth Jain, Paul R. Rosenbaum, Joseph G. Reiter, Alexander S. Hill, David A. Wolk , et al. · 2022

Matching One Sample According to Two Criteria in Observational Studies Open

Bo Zhang, Dylan S. Small, Karen B. Lasater, Matthew D. McHugh, Jeffrey H. Silber , et al. · 2021

Multivariate matching has two goals (i) to construct treated and control groups that have similar distributions of observed covariates, and (ii) to produce matched pairs or sets that are homogeneous in a few key covariates. When there are …

Matching One Sample According to Two Criteria in Observational Studies Open

Bo Zhang, Dylan S. Small, Karen B. Lasater, Matthew D. McHugh, Jeffrey H. Silber , et al. · 2021

Multivariate matching has two goals: (i) to construct treated and control groups that have similar distributions of observed covariates, and (ii) to produce matched pairs or sets that are homogeneous in a few key covariates. When there are…

Matching One Sample According to Two Criteria in Observational Studies Open

Bo Zhang, Dylan S. Small, Karen B. Lasater, Matthew D. McHugh, Jeffrey H. Silber , et al. · 2021

Multivariate matching has two goals (i) to construct treated and control groups that have similar distributions of observed covariates, and (ii) to produce matched pairs or sets that are homogeneous in a few key covariates. When there are …

Reinforced Designs: Multiple Instruments Plus Control Groups as Evidence Factors in an Observational Study of the Effectiveness of Catholic Schools Open

Bikram Karmakar, Dylan S. Small, Paul R. Rosenbaum · 2021

Absent randomization, causal conclusions gain strength if several independent evidence factors concur. We develop a method for constructing evidence factors from several instruments plus a direct comparison of treated and control groups, a…

Alzheimer’s Dementia After Exposure to Anesthesia and Surgery in the Elderly Open

Jeffrey H. Silber, Paul R. Rosenbaum, Joseph G. Reiter, Alexander S. Hill, Siddharth Jain , et al. · 2020

Objective: The aim of this study was to determine whether surgery and anesthesia in the elderly may promote Alzheimer disease and related dementias (ADRD). Background: There is a substantial conflicting literature concerning the hypothesis…

Using Medicare claims in identifying Alzheimer's disease and related dementias Open

Siddharth Jain, Paul R. Rosenbaum, Joseph G. Reiter, Geoffrey J. Hoffman, Dylan S. Small , et al. · 2020

Introduction This study develops a measure of Alzheimer's disease and related dementias (ADRD) using Medicare claims. Methods Validation resembles the approach of the American Psychological Association, including (1) content validity, (2) …

Evaluating the Costs and Outcomes of Hospital Nursing Resources: a Matched Cohort Study of Patients with Common Medical Conditions Open

Karen B. Lasater, Matthew D. McHugh, Paul R. Rosenbaum, Linda H. Aiken, Herbert L. Smith , et al. · 2020

Rejoinder: Matching Methods for Observational Studies Derived from Large Administrative Databases Open

Ruoqi Yu, Jeffrey H. Silber, Paul R. Rosenbaum · 2020

Matching Methods for Observational Studies Derived from Large Administrative Databases Open

Ruoqi Yu, Jeffrey H. Silber, Paul R. Rosenbaum · 2020

We propose new optimal matching techniques for large administrative data sets. In current practice, very large matched samples are constructed by subdividing the population and solving a series of smaller problems, for instance, matching m…

Causal Inference With Two Versions of Treatment Open

Raiden B. Hasegawa, Sameer K. Deshpande, Dylan S. Small, Paul R. Rosenbaum · 2020

Causal effects are commonly defined as comparisons of the potential outcomes under treatment and control, but this definition is threatened by the possibility that either the treatment or the control condition is not well defined, existing…

Valuing hospital investments in nursing: multistate matched-cohort study of surgical patients Open

Karen B. Lasater, Matthew D. McHugh, Paul R. Rosenbaum, Linda H. Aiken, Herbert Smith , et al. · 2020

Background There are known clinical benefits associated with investments in nursing. Less is known about their value. Aims To compare surgical patient outcomes and costs in hospitals with better versus worse nursing resources and to determ…

Anticipated and Discovered Patterns of Response Open

Paul R. Rosenbaum · 2020

Design sensitivity is used to quantify the effectiveness of devices discussed in Chap. 5 . Several of those devices anticipate a particular pattern of results, perhaps coherence among several outcomes, or a dose–response relationship. To w…

Risk-Set Matching Open

Paul R. Rosenbaum · 2020

When a treatment may be given at various times, it is important to form matched pairs or sets in which subjects are similar prior to treatment but avoid matching on events that were subsequent to treatment. This is done using risk-set matc…

Some Counterclaims Undermine Themselves Open

Paul R. Rosenbaum · 2020

A counterclaim disputes the claim that an association between treatment received and outcome exhibited reflects an effect caused by the treatment. Some counterclaims undermine themselves. A supplemental statistical analysis may demonstrate…

Matching Without Groups Open

Paul R. Rosenbaum · 2020

Optimal matching without groups, or optimal nonbipartite matching, offers many additional options for matched designs in both observational studies and experiments. One starts with a square, symmetric distance matrix with one row and one c…

Opportunities, Devices, and Instruments Open

Paul R. Rosenbaum · 2020

What features of the design of an observational study affect its ability to distinguish a treatment effect from bias due to an unmeasured covariate u ij? This topic, which is the focus of Part III of the book, is sketched in informal terms…

Choice of Test Statistic Open

Paul R. Rosenbaum · 2020

The choice of one test statistic rather than another affects the design sensitivity, as it affects the power and efficiency of a randomization test. This is demonstrated by computing the design sensitivity for several competing test statis…

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