Risk Management and Insurance Review publishes applied research, opinion and discussion in the field of risk and insurance. The Review’s “Feature Articles” section includes original research involving applications and applied techniques. The section “Perspectives” provides new insights on research literature, business practice and public policy, while “Educational Insights” serves as a repository of high-caliber model lectures in risk and insurance, along with articles discussing and evaluating instructional techniques.
Editor: Mary A. Weiss
JIM advances an understanding of the issues facing global enterprises and management as they impact both theory and practice. JIM publishes theoretical and empirical research addressing international business strategy, comparative and cross-cultural management, risk management, organizational behavior, and human resource management, among others.
The Journal of International Consumer Marketing examines consumer and organizational buyer behavior on a cross-cultural/national and global scale combining up-to-date research with practical applications to help you develop an action plan for successful marketing strategy development.
Editor: Anthony DiBenedetto
JGSMS endeavors to be a “global bridge” connecting marketing scholars throughout the world. JGSMS has an Asian base, but a global scope. We publish high-quality scholarly articles on marketing written by contributors representing the leading academic authors from Asia and worldwide.
Editor: Anthony DiBenedetto
JEB focuses on theoretical and applied research in economics and finance in areas such as corporate finance, asset pricing, monetary and fiscal theory and policy, financial institutions and markets, and industrial organization. JEB is published six times per year.
Editor: Kenneth J. Kopecky
Published six times a year with two special supplements, Health Services Research (HSR) is HRET’s flagship publication and an official journal of Academy Health. Rated as one of the top journals in the field, HSR publishes outstanding articles reporting the findings of original investigations that expand understanding of the wide-ranging field of health care and help improve the health of individuals and communities.
Co-Editor-in-Chief: Jacqueline S. Zinn
The Data Envelopment Analysis Journal, the official journal of the International Data Envelopment Analysis Society, publishes theoretical and applied research advancing the use of Data Envelopment Analysis (DEA) as a methodology for improving organizational performance.
Editor: Rajiv Banker
Scott Bruce, a PhD student at the Fox School of Business, publishes in top statistics research journal, Biometrics.
Researchers are up to their elbows in data. But new methods are needed to address the increasing size and complexity of modern data structures, especially those with time-varying dynamics.
“Frequently, with biomedical experiments, you have time series data from many different participants, along with other clinical and behavioral information for each,” explains Scott Bruce, a fifth-year PhD student in the Department of Statistical Science at the Fox School.
“However,” he continues, “much of the statistical literature focuses on the analysis of a single time series, so there is a need for new theory and methods that can analyze more complex data generated from these kinds of modern biomedical experiments.”
Bruce’s article on his recent research—under the advisement of Dr. Robert Krafty (University of Pittsburgh) and Dr. Cheng Yong Tang (Temple University)—was accepted for publication by the prestigious statistics journal, Biometrics (and appears online through “Biometrics Early View”). He has developed a new method called “conditional adaptive Bayesian spectrum analysis,” or CABS, which can be used to analyze associations between the dynamics of time series data and other data of interest.
The University of Pittsburgh’s AgeWise Caregiver Study, which examined the relationship between stress and sleep in older adults serving as the primary caregiver for an ill spouse, was the motivation for Bruce’s research. Study participants were monitored during a night of sleep to obtain their heart rate variability time series data, and they completed a questionnaire in order to formulate an individualized sleep score (the Pittsburg Sleep Quality Index).
The goal was to measure the association between physiological stress captured in the heart rate variability data and sleep quality measured by the PSQI score.
“This new method allows you to analyze these associations between the covariates and the time series,” explains Bruce. “It properly reflects the temporally-evolving nature of the relationship and helps us better understand dynamic biological processes. Researchers and practitioners who study time series data in conjunction with other types of data will be interested in this work.”
Bruce and his collaborators also developed user-friendly functions available in MATLAB that allow researchers and practitioners to use CABS in their own work. It’s available at the Biometrics website.