The project topics listed below are provided as examples; these may or may not be offered, and additional projects may be offered instead. Likewise, the list of program faculty may differ in any given summer.
The role of cultural versus structural factors in predicting disease screening, among older Latina women: Students will learn the various steps involved in data analysis, including generating descriptive statistics, and will apply and compare several methods to analyze data, such as hierarchical regression that rely on understanding the issues of older Latina women.
Adjusting for sampling and selection bias in autopsy studies of Alzheimer’s disease: Students will use data from the National Alzheimer's Coordinating Center database to analyze the relationship between neuropathological measures at autopsy and trajectory of clinical decline prior to death. They will apply methods to adjust for right truncation of the cohort due to restriction to autopsy cases, and for selection bias associated with autopsy consent. They will meet with Dr. Wisniewski at the NYU Alzheimer’s Center (see letter) to understand the substantive issues and the current understanding.
Inter-relationships between weight status, socioeconomic factors, and later-life cognitive outcomes: Students will conduct a literature review and formulate tractable research questions relating to later-life cognitive deficits. They will download, link, and quality-check, large-scale public-use data sources such as the Health and Retirement Survey and the National Health and Nutrition Examination Surveys. They will conduct descriptive analyses and advanced regression analyses.
Changing interactions with technologies over the lifecourse: Students will investigate which health topics are discussed or searched for online at different ages, and how this relates to health behaviors, risks and outcomes such as obesity, sleep, alcohol and tobacco consumption. Students will use social network data in conjunction with machine learning and other modeling approaches.
The association between daily changes in financial strain and health and its interaction with aging: Students will learn how to manage and conduct basic descriptive statistics utilizing a publicly available data source that is informative about finances, health and aging. Students will learn how to interpret data on the impact of financial strain on health and health behaviors of individuals in midlife.
Behavioral health practices of minority elder cancer survivors: Students will use qualitative and quantitative methods to explore the behavioral health practices of minority elder cancer survivors, such as factors that may contribute to older adults being lost to follow up care during the cancer disease trajectory. Students will learn various aspects of study procedures including strategies involved in sample recruitment, coding of interviews and data analysis of questionnaires and surveys.
Effects of age on cancer treatment outcomes in clinical trials and observational studies: Students will elucidate the effects of age in addition to the effects of treatments (and of other covariates that include clinical and laboratory measurements). Cancer incidence increases with age and survival is generally age related. Students will learn how data are collected, managed, and analyzed from clinical trials and from observational studies. They will apply statistical methods and models such as logistic regression and censored data methods. They will learn how to apply these methods in clinical trials in cancer and observational data in lung cancer and will read relevant preliminary studies.
Implementing Evidence-based Informed Consent Practices to Address the Risk of Alzheimer’s, Dementia, and Cognitive Impairment in Clinical Trials with Older Adults: This study will foster ethical research via informed consent with people who have Alzheimer’s disease or cognitive impairment. Students will analyze longitudinal survey data from the three-arm randomized controlled trial. They will learn key aspects of reporting survey data (e.g., response rates, checking randomization assumption, reporting demographic characteristics of respondents). They will examine data based on the consolidated framework for implementation research using regression analyses.
Causal Inference in aging research: Aging research is complicated by the fact that many of the causal processes that affect physical and cognitive processes later in life are based on events that occurred much earlier in life or behaviors that have been ongoing for years. Students will learn to discriminate between the types of questions they can answer confidently with existing data and those that require additional assumptions. They will contribute to a broader causal inference software project that Dr. Hill is leading to build in features to help researchers using the software to better understand the assumptions they are making and to report these assumptions transparently.
Factors associated with neurocognitive and/or psychiatric conditions among older, HIV+ adults: Recent data indicate that the incidence and prevalence of HIV/AIDS among individuals ≥50 continue to increase. Students will investigate the social, cultural and structural factors (e.g. poverty, isolation) that increase vulnerabilities to psychiatric and neurocognitive health states among older HIV+ individuals. Additionally, they will identify factors (e.g. specialist care provider availability, social integration, social support, social networks) that foster greater resiliency to negative mental health outcomes, thereby enabling a more nuanced understanding of both the clinical and social service needs of older HIV+ individuals that will significantly impact their quality of life and mental and physical health.
Design of N-of-1 trials for rehabilitation research: Students will learn about the difference between randomized controlled trials and single subject design, and how a well-designed N-of-1 trial can help mitigate limitations of the single subject design. Students will be involved in research projects such as post-stroke rehabilitation that adopt single case designs. They will meet with other aging researchers to discuss the possible use of this design in other studies of aging-related diseases.
Aging in “Cancer Alley” and its effects on health disparities: Students will examine whether aging in the area along the Mississippi River between Baton Rouge and New Orleans exacerbates health disparities compared to those living in other Louisiana parishes. Students will use the Health and Retirement Study Restricted Data to geocode respondents, and statistical and epidemiological modeling to compare physical and mental health outcomes of respondents living in these two types of parishes. Another project will be about Katrina@10, an NICHD-funded research program examining health disparities among disaster-exposed populations. This includes data from three longitudinal cohort studies and explores the impact of major social disruptions and dislocations on aging populations.
Infectious disease outcomes (i.e., HIV, BV, or HCV) among older versus younger people who use drugs: Students will conduct a literature review, develop a research question related to infectious disease outcomes in aging populations who use drugs, and plan an analysis. They will work with cross-sectional and/or case-control studies. They will meet with faculty mentor, D. Duncan, to discuss the substantive and design issues and challenges in studying these populations.
Evaluation of how social determinants of health and access to health care services are related to hospitalizations and emergency department visits over time: Health and Retirement Study (HRS), a longitudinal panel study of about 20,000 adults funded by NIA and the Social Security Administration will be analyzed using statistical/econometric methods to evaluate how factors such as social determinants of health and access to health care services are related to hospitalizations and emergency department visits over time. The proposed analysis will take into account differences in outcomes (risk of hospitalizations and emergency department visits) by health insurance coverage status, clinically-relevant dyads and triads of chronic health conditions, ethnicity and race.
Interdependence of key life course events in the arenas of workforce development and retirement: Students will learn modern “sequence analysis” methods and apply them to specific questions that seek to understand the potential relationships between early home life and subsequent labor force attachment and retirement trajectories.
Trajectories of cognitive decline in relationship with tooth loss: Students will use the Health Retirement Study and the English Longitudinal Study of Aging to study this question. Students will learn how to access publicly available data, data management, and data analysis. In particular, they will learn about correlated data that arise across time and from multiple tooth outcomes.
Assessment of tobacco product prevalence, progression, and transition among U.S. older adults: Students will use data extracted from the Population Assessment of Tobacco Use and Health study. They will learn and apply latent variable methods to evaluate whether and how users of one tobacco type transition to other products, adjusting for sampling bias, nonresponse bias, and confounding. They will investigate how age plays a role in these transitions and biases.
If you have any questions about the program, please contact the program coordinator at GPH.Pipelines@nyu.edu.
The Pipelines into Quantitative Aging Research (PQAR) Summer Program is funded by the National Institute on Aging (NIA) grant R25AG06793101.