Heather Morrison
About Heather Morrison
Heather Morrison serves as the Director of Data Collection and Management at Decision Information Resources, bringing over 20 years of experience in managing large-scale research projects, including work with the National Center for Health Statistics.
Current Role at Decision Information Resources
Heather Morrison serves as the Director of Data Collection and Management at Decision Information Resources. She has held this position since 2017, contributing to the organization from Houston, Texas. In her role, she specializes in managing data collection processes and ensuring the integrity of research methodologies.
Previous Experience at NORC at the University of Chicago
Heather Morrison has extensive experience at NORC at the University of Chicago, where she worked in various capacities from 2001 to 2016. Her roles included Survey Specialist, Survey Director, and Senior Survey Director. During her tenure, she managed large-scale research projects and contributed to significant initiatives, including overseeing projects for the National Center for Health Statistics.
Educational Background
Heather Morrison earned her Master of Arts degree in Philosophy from Washington University in St. Louis, where she studied from 1991 to 1993. She also holds a bachelor's degree in Philosophy and Psychology from Albion College, which she attended from 1987 to 1991. Additionally, she continued her studies at Washington University in St. Louis from 1993 to 2000.
Specialization in Data Collection
Heather Morrison specializes in both quantitative and qualitative data collection modes. With over 20 years of experience in managing large-scale research projects, she has developed a strong expertise in designing and implementing effective data collection strategies.
Publications and Contributions
Heather Morrison co-authored a publication focused on improving measures of sexual and gender identity in surveys. Her work in this area reflects her commitment to enhancing research methodologies and ensuring accurate representation in data collection.