Jody Schimmel Hyde, PhD, is a Research Scientist in the Survey Research Center (SRC) of the Institute for Social Research (ISR) at the University of Michigan (UM). She is a co-investigator and an associate director of the Health and Retirement Study. Dr. Schimmel Hyde’s research focuses on financial independence, employment, and public programs to support… Continue reading Jody Hyde
Research Theme: Methodology
Hoda Rahmani
Hoda Rahmani is a Postdoctoral Research Fellow at the Institute for Research on Innovation and Science (IRIS) at the University of Michigan. She earned her PhD and Master’s degrees in Industrial and Systems Engineering from Ohio University, with research focusing on applying machine learning and optimization techniques to complex systems.
Novel Methods to Inform mHealth Interventions for Substance Use
This project aims to address the need for robust, rigorous and computationally efficient methods for optimizing Just-In-Time Adaptive Interventions (JITAIs) to prevent and treat substance use disorders (SUD). Although the proposed methods are motivated by micro randomized trials (MRTs) in SUD, they can be extended to observational studies and employed to develop effective JITAIs in… Continue reading Novel Methods to Inform mHealth Interventions for Substance Use
New York City Housing and Vacancy Survey (NYCHVS)
The New York City Housing and Vacancy Survey (NYCHVS) is a citywide, representative survey of New York City’s housing stock and population conducted about every three years. The NYCHVS collects data in neighborhoods, in all five boroughs, and focuses on representing all New Yorkers—regardless of who they are or where they live. All of this… Continue reading New York City Housing and Vacancy Survey (NYCHVS)
Improving Measurement of Community Safety Perceptions with Enhanced Data Inclusivity and Novel Use of Small Area Estimation through Population – Based Hybrid Sampling: A Pilot Study in Detroit, Michigan
The proposed study aims to implement a pilot project in the City of Detroit (n=1,200) with a novel, yet practical sampling approach designed to maximize coverage of microgeographies (Census block groups in our case) as well as inclusivity of groups who may be underrepresented in traditional sample surveys due to, for example, nonresponse and may… Continue reading Improving Measurement of Community Safety Perceptions with Enhanced Data Inclusivity and Novel Use of Small Area Estimation through Population – Based Hybrid Sampling: A Pilot Study in Detroit, Michigan
Determining What is Right for Whom: A Hybrid Experimental Clinical Trial of Tailored Intervention Sequencing to Maximize Effectiveness of PTSD Treatment
Cognitive Processing Therapy (CPT) and Prolonged Exposure (PE) are the most effective treatments for PTSD; however, up to 41% of patients do not improve significantly. It remains unclear how best to adapt treatment when patients show early non-response or struggle with between-session homework. To address this, our team developed the Hybrid Experimental Design (HED), a… Continue reading Determining What is Right for Whom: A Hybrid Experimental Clinical Trial of Tailored Intervention Sequencing to Maximize Effectiveness of PTSD Treatment
A sensitivity analysis framework for generalizing randomized clinical trial results in the presence of unmeasured treatment effect modifier
Randomized controlled trials (RCTs) are the gold standard for assessing interventions for preventing and treating cancer, but their external validity is only guaranteed if the trial participants are a random sample from the target population. Unfortunately, most cancer-related RCTs use convenience samples, not probability samples, and differences between the trial sample and the target population… Continue reading A sensitivity analysis framework for generalizing randomized clinical trial results in the presence of unmeasured treatment effect modifier
Improving Inclusivity of Alzheimer’s Disease and Related Dementias Research for Asian Americans and Latinx through Nationally Representative Hybrid Sampling
Alzheimers Disease and Related Dementias (ADRD), set as a public health priority by the World Health Organization, is one of the leading causes of death in the U.S.; however, a dearth of ADRD research data that consider dynamics across racial/ethnic groups beyond minimum standard racial/ethnic categories is detrimental to understanding a comprehensive picture of the… Continue reading Improving Inclusivity of Alzheimer’s Disease and Related Dementias Research for Asian Americans and Latinx through Nationally Representative Hybrid Sampling
A Next Generation Data Infrastructure to Understand Disparities across the Life Course
This project aims to further advance capabilities in the social sciences (broadly defined) to collect data on the daily lives of families and individuals. These data will be more accurate, more granular, and more complete than has been possible to obtain in traditional survey-based research until now. The context for this is the Understanding America… Continue reading A Next Generation Data Infrastructure to Understand Disparities across the Life Course
UAS-CLEAR: A new nationally representative longitudinal study of caregiving experiences and well-being across the lifecourse
Family caregivers are essential to the nations well-being and economy yet little information exists regarding the daily lives of Alzheimer’s Disease and Related Dementias (ADRD) and non-ADRD caregivers across the diverse social partners who provide care. The present study develops and administers new survey instruments in the Understanding America Study (UAS) (https://uasdata.usc.edu/index.php) to identify caregivers… Continue reading UAS-CLEAR: A new nationally representative longitudinal study of caregiving experiences and well-being across the lifecourse