MPSDS JPSM Seminar Series
February 1, 2023
12:00 - 1:00 EST

The Role of Data Collection in Population Science: Contemporary Studies from ABCD to HBCD

Abstract

Recently nationwide consortiums of multiple research sites have conducted multi-modal, longitudinal cohort studies and provided unprecedented data sources for population science research. For example, the Adolescent Brain Cognitive Development (ABCD) Study has collected data from 11,880 children ages 9-10 across 21 U.S. research sites, as the largest long-term study of brain development and child health; and the Healthy Brain and Child Development (HBCD) Study will enroll 7,500 pregnant women across 25 research sites and follow them from pregnancy through early childhood, as the largest long-term study of early brain and child development in the U.S. Both studies aim to reflect the sociodemographic diversity of the target population to enable characterization of natural variability and trajectories. Without probability sampling as the touchstone for randomization-based inferences, the data quality and analysis validity require rigorous evaluations and potentially rely on untestable assumptions. The data collection process also presents various challenges during practical operation.

In this talk, I look into both inference and design schemes to study the impact of data collection on population science. First, using the ABCD study as an example of secondary data analysis, I discuss inference approaches focusing on multilevel regression and poststratification for population generalizability and latent subgroup detection for population heterogeneity in brain activity and association studies. Second, I introduce the HBCD study design. HBCD also aims to include individuals demographically and behaviorally similar to those in the substance exposure group, but without exposure, to enable valid causal inference in a non-experimental study design. I discuss our proposed weighting, matching, and modeling strategies to leverage analysis goals to inform the design and dashboard monitoring for adaptive sample enrollment.

Bio

Yajuan Si is a Research Associate Professor in the Institute for Social Research at the University of Michigan. Dr Si’s research lies in cutting-edge methodology development in streams of Bayesian statistics, linking design- and model-based approaches for survey inference, missing data analysis, confidentiality protection involving the creation and analysis of synthetic datasets, and causal inference with observational data.

Michigan Program in Survey and Data Science (MPSDS)
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

Summer Institute in Survey Research Techniques (SISRT)
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The program teaches state-of-the-art practice and theory in the design, implementation, and analysis of surveys. The Summer Institute in Survey Research Techniques has presented courses on the sample survey since the summer of 1948, and has offered such courses every summer since. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

The Summer Institute uses the sample survey as the basic instrument for the scientific measurement of human activity. It presents sample survey methods in courses designed to meet the educational needs of those specializing in social and behavioral research such as professionals in business, public health, natural resources, law, medicine, nursing, social work, and many other domains of study.