340.775.01
Measurement Theory and Techniques in Epidemiology
Location
East Baltimore
Term
3rd Term
Department
Epidemiology
Credit(s)
4
Academic Year
2024 - 2025
Instruction Method
In-person
Tu, Th, 10:30 - 11:50am
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
340.728 (AMDACS) or 340.774 Adv. Theory & Methods in Epi, or 140.658 Statistics for Psychosocial Research: Structural Models
Modern peer-reviewed research opines for advanced, novel statistical methods to address important, increasingly complex scientific questions about the multivariate world. This course provides overviews of common and novel sources of measurement in epidemiology and delves into applications of advanced analytic models that are used to represent constructs from measures. Examples are taken from published epidemiologic research. The course will review necessary assumptions and appropriateness of models of construct representation given available data. From this course, students will learn to interpret, apply, and gauge the appropriateness of particular measurement methods.
Reviews concepts, key assumptions, and published applications of measurement theory, including true scores and counterfactual outcomes, latent variables, and validity. Explores novel applications of item response theory to refinement of measures, assessment of differential item functioning, and calibration of metrics across diverse samples. Topics include analysis of novel types of data (biomarkers, high-dimensional data, administrative records, genetics), item response theory, latent growth curve models for longitudinal data and their extensions, and cross-study statistical harmonization and co-calibration. Draws examples from epidemiologic applications in the behavioral and social sciences. Offers students opportunities for applying lessons from didactic lectures in a laboratory setting using prepared examples.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Analyze categorical data using item response theory and interpret results
- Analyze and interpret latent growth curve models and extensions
- Analyze and interpret bivariate dual change score models
- Conduct integrative data analysis of constructs across multiple studies and time points that feature differing measures
- Identify and correct for differential item functioning
- Describe the place of one's own research along the continuum from qualitative to quantitative analysis
- Recognize measurement errors and nuances of measurement intrinsic to biomarker data, high-dimensional data (e.g., accelerometry and MRI data), genetic data, interviews and survey questionnaires, administrative data, and group-level aggregations of data.
- Briefly describe aspects of specific types and sources of measurements common in epidemiology, including genetics, surveys, administrative records, high-dimensional data, biological markers, and census-level data.
Methods of Assessment
This course is evaluated as follows:
- 50% Lab Assignments
- 35% Final Project
- 15% Quizzes