A5102731950- Comparative International Legal Studies
- Legal processes and jurisprudence
- Family and Matrimonial Law
- Criminal Justice and Penology
- Ethics and bioethics in healthcare
- Administrative Law and Governance
- Human Rights and Immigration
- Comparative constitutional jurisprudence studies
- Merger and Competition Analysis
- Advanced Causal Inference Techniques
- Statistical Methods and Bayesian Inference
- Law, logistics, and international trade
- Medication Adherence and Compliance
- Law, Economics, and Judicial Systems
- Blood Pressure and Hypertension Studies
- Labor Law and Work Dynamics
- Corporate Governance and Law
- Medical Malpractice and Liability Issues
- Survey Methodology and Nonresponse
- European and International Contract Law
- Finance, Taxation, and Governance
- Statistical Methods and Inference
- Electoral Systems and Political Participation
- European Criminal Justice and Data Protection
- Social Sciences and Policies
Etsy (United States)
2022
Harvard University
2017-2021
Frontier Agriculture (United Kingdom)
2018
Harvard University Press
2017
Hospital Británico
2000
The popularity of online surveys has increased the prominence using sampling weights to enhance claims representativeness. Yet, much uncertainty remains regarding how these should be employed in survey experiment analysis: they used? If so, which estimators are preferred? We offer practical advice, rooted Neyman–Rubin model, for researchers working with experimental data. examine simple, efficient estimators, and give formulas their biases variances. provide simulations that as well real...
Unplanned hospital readmissions are a major source of morbidity among dialysis patients, in whom the risk readmission is exceptionally high. The contribution facility staffing to has been largely overlooked.Using annual data patients from United States Renal Data System 2010 2013, we assessed facilities with significantly worse (SW) and nonsignificant (NS) standardized ratio (SRR). SRR estimates were adjusted for patient factors, past year comorbidities, index hospitalization...
Profiling or evaluation of health care providers involves the application statistical models to compare each provider's performance with respect a patient outcome, such as unplanned 30-day hospital readmission, adjusted for case-mix characteristics. The nationally adopted method is based on random effects (RE) hierarchical logistic regression models. Although RE are sensible modeling data, novel high dimensional fixed (FE) have been proposed which may be well-suited objective identifying...
Summary One of the most significant barriers to medication treatment is patients’ non-adherence a prescribed regimen. The extent impact poor adherence on resulting health measures often unknown, and typical analyses ignore time-varying nature adherence. This article develops modeling framework for longitudinally recorded modeled as function Our framework, which relies normal Bayesian dynamic linear models (DLMs), accounts covariates such non-dynamic baseline characteristics. Standard...
Profiling analysis aims to evaluate health care providers by modeling each provider's performance with respect a patient outcome, such as unplanned hospital readmission. High-dimensional regression models are used in profiling risk-adjust for case-mix covariates. Case-mix covariates typically ascertained from administrative databases inherently error-prone. We examine the impact of measurement error (ME) on models. The results show that even though models' coefficient estimates biased, this...
The self‐controlled case series (SCCS) method is useful for estimating the relative incidence (RI) of acute events, such as adverse events during a specified risk period following an exposure (e.g. six‐week after vaccinations or 30‐day infection‐related hospitalizations). In practice, “optimal” unknown and must be specified. To date, two approaches are available to guide specification period. Both methods do not fully utilize nature bias due misspecification, which date has been...
The analysis of individual X-ray sources that appear in a crowded field can easily be compromised by the misallocation recorded events to their originating sources. Even with small number sources, nonetheless have overlapping point spread functions, allocation is complex task subject uncertainty. We develop Bayesian method designed sift high-energy photon from multiple leveraging differences spatial, spectral, and temporal signatures. probabilistically assigns each event given source. Such...