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Maxwell School News and Commentary

Bei Yu and co-authors publish study on exaggerated claims in press releases about health research

October 19, 2021
The result of an NSF-funded project, the authors propose a Natural Language Processing approach to identify when press releases overstate causal claims for research that was originally observational and designed to establish correlational findings.

*Move to News Article* Emily Wiemers to study challenges of caring for aging parents amid pandemic

October 11, 2021
Wiemers, associate professor of public administration and international affairs, will serve as principal investigator for a two-year, NIH-funded study of the challenges to those caring for aging parents amid the COVID-19 pandemic. The project also includes researchers at Bowling Green State University.

See related: COVID-19

Researchers examine COVID’s toll on NYC children’s health, education

October 6, 2021
Amy Ellen Schwartz, professor of economics and public administration and international affairs, is one of two principal investigators for a five-year research project to examine how, over time, COVID-19 has affected children’s health and education in New York City. Maxwell School faculty colleague Michah W. Rothbart is among the co-investigators.�Funded by the National Institutes of Health, the $3.5 million study is a collaboration by researchers at Syracuse University, New York University and the New York City Department of Health and Mental Hygiene.

NIH awards $1.95M to study state-level COVID policies, mental health

October 1, 2021
Shannon Monnat, associate professor of sociology and Lerner Chair for Public Health Promotion, is the principal investigator for a five-year research project that will examine the impacts of state COVID-19 mitigation policies on adult psychological health, drug overdose and suicide. The project is funded with $1.95 million from the National Institutes of Health.

See related: State and Local

WP 187 Bayesian Spatial Bivariate Panel Probit Estimation

August 11, 2021
This paper formulates and analyzes Bayesian model variants for the analysis of systems of spatial panel data with binary dependent variables.

See related: Econometrics

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