Ronald R. Rindfuss, Minja K. Choe, Noriko O. Tsuya, Larry L. Bumpass, Emi Tamaki
DEMOGRAPHIC RESEARCH, 32(1) 797-828, Mar, 2015 Peer-reviewed
BACKGROUND
In developed countries, response rates have dropped to such low levels that many in the population field question whether the data can provide unbiased results.
OBJECTIVE
The paper uses three Japanese surveys conducted in the 2000s to ask whether low survey response rates bias results. A secondary objective is to bring results reported in the survey response literature to the attention of the demographic research community.
METHODS
Using a longitudinal survey as well as paradata from a cross-sectional survey, a variety of statistical techniques (chi square, analysis of variance (ANOVA), logistic regression, ordered probit or ordinary least squares regression (OLS), as appropriate) are used to examine response-rate bias.
RESULTS
Evidence of response-rate bias is found for the univariate distributions of some demographic characteristics, behaviors, and attitudinal items. But when examining relationships between variables in a multivariate analysis, controlling for a variety of background variables, for most dependent variables we do not find evidence of bias from low response rates.
CONCLUSIONS
Our results are consistent with results reported in the econometric and survey research literatures. Low response rates need not necessarily lead to biased results. Bias is more likely to be present when examining a simple univariate distribution than when examining the relationship between variables in a multivariate model.
COMMENTS
The results have two implications. First, demographers should not presume the presence or absence of low response-rate bias; rather they should test for it in the context of a specific substantive analysis. Second, demographers should lobby data gatherers to collect as much paradata as possible so that rigorous tests for low response-rate bias are possible.