Jennifer Dykema

My research focuses on survey research methodology, identifying sources of errors produced in the process of gathering standardized measurements and developing and implementing methods to reduce those errors. This work includes projects supported by extramural funding from NSF and NIH and examines three main areas of inquiry: interviewer-respondent interaction, questionnaire design, and methods to increase response rates. In a current project funded by NSF, we are using data and transcripts from a health survey measuring barriers and facilitators to participating in medical research among underrepresented groups to examine the interplay between the characteristics of survey questions, behaviors of interviewers and respondents, and the socio-demographic attributes of interviewers and respondents. In my role as Faculty Director of the University of Wisconsin Survey Center (UWSC), I oversee a program of methodological research that incorporates experiments and evaluations in ongoing projects to address critical issues such as response rates and nonresponse bias, the influence of field procedures on costs, and the consequences of various design and implementation decisions on data quality. Examples of recent projects include: what incentive combinations improve survey response; does straightlining behavior vary by mode in mail-web mixed mode studies; how should sample members be addressed in postal surveys; and how does data quality vary for agree-disagree versus construct-specific questions.

Selected Publications:

Dykema, Jennifer, John Stevenson, Cameron P. Jones, and Brendan Day. “Guaranteed Incentives and Prize Drawings: Effects on Participation, Data Quality, and Costs in a Web Survey of College Students on Sensitive Topics.” Social Science Computer Review 42, no. 3 (2024): 777-793.

Garbarski, Dana, Jennifer Dykema, Cameron P. Jones, Tiffany S. Neman, Nora Cate Schaeffer, and Dorothy Farrar Edwards. “Questioning Identity: How a Diverse Set of Respondents Answer Standard Questions About Ethnicity and Race.” Field Methods 36, no. 2 (2024): 113-130.