Jesse Chandler
Human Services

Jesse Chandler

Senior Data Analyst
Name Pronunciation JEH-see CHAND-lr
Pronouns he/his

Jesse Chandler is a senior data analyst with interests in measurement and methodology. He has published extensively on best practices for using nonprobability samples, with an emphasis on online labor markets, and potential sources of measurement error in survey design. More recently, he has led projects investigating how people interpret data visualizations (including dashboards and the results of inferential statistical tests) and incorporate this information into decision making.

Since joining Mathematica in 2015, Chandler has led data collection and analysis for survey experiments testing the effectiveness of survey instruments for the National Center for Science and Engineering Statistics and of different data visualizations for the Institute of Education Sciences. For the Rehabilitation Research and Training Center on Disability Statistics and Demographics, funded by the National Institute on Disability, Independent Living, and Rehabilitation Research, he has conducted projects testing the feasibility of different modes of technology to collect information from people with disabilities. Chandler also has deep knowledge about measuring training needs and effectiveness and has directed surveys supporting programs offered by the Centers for Medicare & Medicaid Services targeting medical practices (for the Transforming Clinical Practice Initiative) and accountable care organizations (for the Learning Systems for Accountable Care Organizations project).

Chandler previously led social and traditional media research projects for technology clients at PRIME Research. He holds a Ph.D. in social psychology from the University of Michigan and completed postdoctoral training in psychology and public policy at the Princeton School of Public and International Affairs.

Expertise
  • Data visualization
  • Data quality
  • Behavioral science
  • Nonprobability samples
Focus Area Topics
  • Human Services
  • Disability
  • Statistics and Measurements
  • Early Childhood
  • Quality Measurement
  • Education
  • Effective Data Use
  • Health

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