Jennifer Priestley. Ph.D.

Researchers and practitioners in financial services utilize a wide range of empirical techniques to assess risk and value. In cases where known performance is used to predict future performance of a new asset, the risk of bias is present when samples are uncontrolled by the analyst. Propensity score matching is a statistical methodology commonly used in medical and social science research to address issues related to experimental design when random assignment of cases is not possible. This… Show more

Researchers and practitioners in financial services utilize a wide range of empirical techniques to assess risk and value. In cases where known performance is used to predict future performance of a new asset, the risk of bias is present when samples are uncontrolled by the analyst. Propensity score matching is a statistical methodology commonly used in medical and social science research to address issues related to experimental design when random assignment of cases is not possible. This common method has been almost absent from financial risk modeling and portfolio underwriting, primarily due to the different objectives for this sector relative to medicine and social sciences. In this application note, we demonstrate how propensity score matching can be considered as a practical tool to inform portfolio underwriting outside of experimental design. Using a portfolio of distressed consumer credit accounts, we demonstrate that propensity score matching can be used to predict both account-level and portfolio-level risk and argue that propensity score matching should be included in the methodological toolbox of researchers and practitioners engaged in risk modeling and valuation activities of portfolios of consumer assets, particularly in contexts with limited observations, a large number of potential modeling features, or highly imbalanced covariates. Show less

The perception of Latin as the “best” language has a long history in the West and in the United States. Many Americans view Latin as more logical and more grammatical than English. Other Americans view the study and use of Latin as elitist. When religious convictions are added to linguistic views of Latin, attitudes towards Latin take on a spiritual, and thus more spirited, edge. The present study examines sociolinguistic views about Latin’s status in the religious context of the Catholic Mass.… Show more

The perception of Latin as the “best” language has a long history in the West and in the United States. Many Americans view Latin as more logical and more grammatical than English. Other Americans view the study and use of Latin as elitist. When religious convictions are added to linguistic views of Latin, attitudes towards Latin take on a spiritual, and thus more spirited, edge. The present study examines sociolinguistic views about Latin’s status in the religious context of the Catholic Mass. Through a large-scale online survey, the authors examine how Latin as a language and its use in the Traditional Latin Mass (TLM) are viewed by Catholics. Both quantitative and qualitative data reveal that a positive sociolinguistic view of Latin plays a role in some American Catholics’ affinity for the TLM. Proponents of the TLM support this form of the Mass primarily for religious reasons, but positive views of the Latin language undergird their support. American Catholics who prefer Mass in the vernacular often do so because they view Latin as an impediment to comprehension and participation in the Mass. In addition, they view the use of Latin as elitist and divisive, particular in the current religious climate. The data show a sharp religious divide between “conservative” and “progressive” American Catholics about the question of the use of Latin in Catholic Masses, which present a dilemma for religious leaders in establishing language policy for Masses. Show less

Remdesivir treatment, like most antiviral drugs, is likely to be most effective when used early in the course of coronavirus disease 2019 (COVID-19). Optimal timing of remdesivir for the treatment of COVID-19 remains unclear

As feminizing gender-affirming surgery becomes increasingly accessible, functional outcomes are increasingly relevant. We aimed to develop and validate the first patient-reported outcome questionnaire focusing on postoperative symptomatology and quality of life

The purpose of the study was to understand the impact of involuntary remote working during the early phases of the COVID-19 pandemic on perceived stress and work-related burnout for workers with and without previous experience of remote work. The authors developed a questionnaire, open from March 23rd to May 19th, 2020, incorporating the Perceived Stress Scale, Copenhagen Burnout Inventory, demographic, and work-related questions. This sample consisted of 256 professionals who self-identified… Show more

The purpose of the study was to understand the impact of involuntary remote working during the early phases of the COVID-19 pandemic on perceived stress and work-related burnout for workers with and without previous experience of remote work. The authors developed a questionnaire, open from March 23rd to May 19th, 2020, incorporating the Perceived Stress Scale, Copenhagen Burnout Inventory, demographic, and work-related questions. This sample consisted of 256 professionals who self-identified as working at home during the pandemic. Pandemic restrictions increased perceived stress for all participants, but age and gender had significant effects on stress and burnout. Burnout was most significant for respondents already working remotely before COVID-19. The most significant challenges reported were—communication, collaboration, and time management with colleagues via technology. Working from home may contribute to higher levels of perceived stress and work-related burnout, which questions moves by some employers to make working from home a permanent arrangement Show less

This book seeks to provide a users manual for analytics managers and executives to most effectively collaborate with a university (or universities) to develop pipelines of analytical talent at the undergraduate, masters, and PhD levels. We explain how to navigate the process of engaging in collaborative research with faculty. And discuss how universities can be a resource for “upskilling” your current employees.

Product affinity segmentation discovers groups of customers with similar purchase preferences for cross-selling opportunities to increase sales and customer loyalty. However, this concept can be challenging to implement efficiently and effectively for actionable strategies. First, the nature of skewed and sparse product-level data in the clustering process results in less meaningful solutions. Second, customer segmentation becomes challenging on massive data sets due to the computational… Show more

Product affinity segmentation discovers groups of customers with similar purchase preferences for cross-selling opportunities to increase sales and customer loyalty. However, this concept can be challenging to implement efficiently and effectively for actionable strategies. First, the nature of skewed and sparse product-level data in the clustering process results in less meaningful solutions. Second, customer segmentation becomes challenging on massive data sets due to the computational complexity of traditional clustering methods. Third, market basket analysis may suffer from association rules too general to be relevant for important segments. In this article, we propose to partition customers into groups with their product purchase similarity maximized by detecting communities in the customer–product bipartite graph using the Louvain algorithm. Through a case study using data from a large U.S. retailer, we demonstrate that the proposed method generates interpretable clustering results with distinct product purchase patterns. Comprehensive characteristics of customers and products in each cluster can be inferred with statistical significance since they are essentially driven by products purchased by customers. Compared with the conventional RFM (recency, frequency, monetary) model, the proposed approach leads to higher response rates in the recommendation of products to customers in the same cluster. Our analysis provides greater insights into customer purchase behaviors, improves product recommendation effectiveness, and addresses computational complexity in the context of skewed and sparse big data. Show less

The objective of this study was to describe anatomic and symptomatic outcomes at 5 years or longer after robotic-assisted laparoscopic sacrocolpopexy using very lightweight polypropylene Y-mesh

Is data science a new field of study or simply an extension or specialization of a discipline that already exists, such as statistics, computer science, or mathematics? This article explores the evolution of data science as a potentially new academic discipline, which has evolved as a function of new problem sets that established disciplines have been ill-prepared to address. The authors find that this newly-evolved discipline can be viewed through the lens of a new mode of knowledge production… Show more

Is data science a new field of study or simply an extension or specialization of a discipline that already exists, such as statistics, computer science, or mathematics? This article explores the evolution of data science as a potentially new academic discipline, which has evolved as a function of new problem sets that established disciplines have been ill-prepared to address. The authors find that this newly-evolved discipline can be viewed through the lens of a new mode of knowledge production and is characterized by transdisciplinarity collaboration with the private sector and increased accountability. Lessons from this evolution can inform knowledge production in other traditional academic disciplines as well as inform established knowledge management practices grappling with the emerging challenges of Big Data Show less