Ned English
NORC at the University of Chicago, Chicago
Ned English is a Senior Survey Methodoligist at NORC at the University of Chicago, where he has been since 2002. His expertise lies in the interface between GIS (geographic information systems) and survey methodology, and so has been involved in research including address-based sampling (ABS), targeting rare populations, and the implimentation of the USPS delivery-sequence file (DSF) over the past ten years. Ned has a Master's degree in Geography from the University of Wisconsin-Madison and a Bachelor's degree in Geography from McGill University.
Using Data Analytics for Early Prediction of Response Rate Changes in GSS
Ned English
NORC at the University of Chicago, Chicago
Holly Hagerty
NORC at the University of Chicago
Colm O'Muircheartaigh
NORC at the University of Chicago and The University of Chicago
Chang Zhao
NORC at the University of Chicago
For the past 15 years, researchers at NORC have been predicting final response rates for face-to-face studies by building a model based on detailed field disposition histories from previous projects. In addition to providing the overall prediction of response rate, the model permits more informed case releases, early warning of potential production shortfalls, and the potential to test remedies in real time. Projects have included Making Connections [Annie E Casey Foundation]; the National Social Life, Health, and Aging Project [National Institute on Aging], the General Social Survey [GSS; National Science Foundation], the Survey of Consumer Finances [Federal Reserve] and the National Longitudinal Survey of Youth [Bureau of Labor Statistics]. The GSS has experienced a significant decline in response rates since the 2014 round, paralleling the general sectoral decline in response rates. We demonstrate the use of the model to predict the response rate for the 2018 round of GSS. We show the strengths and weaknesses of the approach during the fieldwork period. Our research is relevant both to those who would benefit from early warnings of response rate issues in field surveys.