Institute for Social Research API | Research Themes

Landscapes of Population Health

Landscapes of Population Health (“Landscapes”) is an interdisciplinary research collective that includes historians, sociologists, psychologists, epidemiologists, and statisticians who bring their expertise in historical and contemporary racial violence and control, environmental justice, epigenomics, and population health to study the link between structural racism and population health. We bring together critical theories from the humanities and… Continue reading Landscapes of Population Health

Silber,Henning

Henning Silber is a Research Assistant Professor in the Survey Methodology Program, located within the Survey Research Center at the Institute for Social Research on the University of Michigan-Ann Arbor (U-M) campus. He earned his PhD from the University of Göttingen (Germany) in 2015 and completed his Habilitation at the University of Mannheim (Germany) in 2023. Before that, he received… Continue reading Silber,Henning

Rigby,David Lee

David Rigby is an Assistant Research Scientist in the Landscapes Lab. David’s research interests focus on understanding processes of racialization, the ways that social dynamics and institutions come to be informed by ideas about race, and the pathways through which historical forms of racial violence and social control shape institutions and cultures, impacting the contemporary… Continue reading Rigby,David Lee

Crossley,Thomas Fraser

Thomas (Tom) Crossley is Research Professor and Director of the Panel Study for Income Dynamics (PSID). Professor Crossley’s research interests include household behavior (particularly consumption and saving behavior), financial security, and living standards; the design, collection and analysis of survey data; and economic measurement more broadly.

Novel Approaches to Adjusting for Population Heterogeneity and Representation in Neuroimaging Studies

Telemedicine and human Brain recovery concept. Grey color palette, copy space for text.

Big data featuring neuroimaging information collected from large population-based samples have spurred the emergence of population neuroscience research. However, traditional methods for neuroscience research are based on nonrepresentative samples that deviate from the target population, such as convenience and volunteer samples. The lack of representativeness may distort association studies of brain-cognition mechanisms. The research team’s… Continue reading Novel Approaches to Adjusting for Population Heterogeneity and Representation in Neuroimaging Studies

Statistical adjustments of sample representation in community-level estimates of COVID-19 transmission and immunity

Rapid kits of Covid-19 Ag test seen on blue background.

Throughout the COVID-19 pandemic, government policy and healthcare implementation responses have been guided by reported positivity rates and vaccination rates in the community. The selection bias of these test data questions their validity as measures of the actual viral incidence in the community and as predictors of clinical burden. Publicly available vaccination data are frequently… Continue reading Statistical adjustments of sample representation in community-level estimates of COVID-19 transmission and immunity

A National Neighborhood Data Resource to Understand Inequities in the Health and Socioeconomic Impacts of COVID-19 in the United States

Seneca Falls, New York city center in early morning

We are only beginning to clarify the ways the COVID-19 pandemic has resulted in substantial changes to American neighborhoods. There has been an excess of permanent business closures, particularly among small neighborhood businesses most vulnerable to social distancing, such as local barbershops and nail salons. COVID-19 outbreaks in late September 2021 caused 2,000 neighborhood schools… Continue reading A National Neighborhood Data Resource to Understand Inequities in the Health and Socioeconomic Impacts of COVID-19 in the United States

Exploring the Use of Deep Learning Neural Networks to Improve Dementia Detection: Automating Coding of the Clock-Drawing Test

An Asian senior man is writing sequence of numbers in a circle (clock graphic) as part of dementia medical check-up.

Alzheimer’s disease and related dementias (ADRD), a leading cause of disability among older adults, has become a critical public health concern. The clock-drawing test, which measures multiple aspects of cognitive function including comprehension, visual spatial abilities, executive function and memory, has been widely used as a screening tool to detect dementia in clinical research, epidemiologic… Continue reading Exploring the Use of Deep Learning Neural Networks to Improve Dementia Detection: Automating Coding of the Clock-Drawing Test

New Approaches to Analyzing Social Media Content for Enhancing Census Bureau Data

Woman using social media microblogging app on her smart phone

There has been substantial interest in whether and how analyses of social media data can add value to social research and the production of official statistics. Some researchers hope that survey findings can be augmented with social media content, while others hope that costs might be reduced and timeliness improved by replacing at least some… Continue reading New Approaches to Analyzing Social Media Content for Enhancing Census Bureau Data