Danielle Battle is a senior researcher at AIR. She has survey methods training along with expertise in the management, construction, and analysis of large datasets. While at the University of Michigan, she conducted nonresponse bias analyses and multiple imputation procedures for the Michigan Recession and Recovery Study.
Since joining AIR, Battle has worked on both the Schools and Staffing Survey, sponsored by the National Center for Education Statistics (NCES), and Project Talent, a national longitudinal study. She has also been involved with data processing for MRRS, SASS and Project Talent, creating data quality control specifications that include data cleaning and editing procedures. She is experienced in the development of weights to compensate for unequal-probability, post-stratification, and non-response over multiple collection waves. Through her work with Project Talent she has experience executing nonresponse unit and item bias analysis, and developing and implementing procedures to link administrative data to sample records. She has also managed questionnaire development through cognitive interviews and instrument testing with the National Household Education Survey. Her experience at AIR includes reviewing national survey data and assisting in the writing and publication of documentation and data summary reports.