title: Using logistic regression to detect item-level non-response bias in surveys.
abstract: This article describes a procedure for evaluating item-level non-response bias in questionnaire items. Specifically, logistic regression is used to determine whether non-responses are random or systematic in nature for one question from the National Educational Longitudinal Study of 1994 concerning drug use behaviors. It turns out that, indeed, non-responses are systematic with males and lower achieving students being more likely to contribute to non-response along with two-way interactions between ethnicity and SES and ethnicity and geographic region. In addition, the magnitude of the potential bias is estimated, which demonstrates that the parameter estimates obtained by assuming that the data are missing at random may be extremely biased, given this frame of reference. Finally, several steps are suggested for evaluating the threat of non-response bias in survey research.
authors.affiliation: 450 Erickson Hall, Michigan State University, East Lansing, MI 48824, USA. wolfee@msu.edu
authors.forename: Edward W
authors.initials: EW
authors.lastname: Wolfe
mesh_terms: D000293:Adolescent; D000465:Algorithms; D015982:Bias; D015331:Cohort Studies; D005260:Female; D005382:Financing, Personal; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D018907:Privacy; D011594:Psychometrics / Q000706:statistics & numerical data*; D012650:Self Disclosure; D019966:Substance-Related Disorders / Q000191:economics / Q000453:epidemiology / Q000523:psychology; D011795:Surveys and Questionnaires