Title: Measuring bias in self-reported data

Authors: Robert Rosenman; Vidhura Tennekoon; Laura G. Hill

Addresses: School of Economic Sciences, Washington State University, P.O. Box 646210, Pullman, WA 99164-6210, USA. ' School of Economic Sciences, Washington State University, P.O. Box 646210, Pullman, WA 99164-6210, USA. ' Department of Human Development, Washington State University, 523 Johnson Tower, Pullman, WA 99164, USA

Abstract: Response bias shows up in many fields of behavioural and healthcare research where self-reported data are used. We demonstrate how to use stochastic frontier estimation (SFE) to identify response bias and its covariates. In our application to a family intervention, we examine the effects of participant demographics on response bias before and after participation; gender and race/ethnicity are related to magnitude of bias and to changes in bias across time, and bias is lower at post-test than at pre-test. We discuss how SFE may be used to address the problem of |response shift bias| – that is, a shift in metric from before to after an intervention which is caused by the intervention itself and may lead to underestimates of programme effects.

Keywords: response bias; response-shift bias; programme evaluation; stochastic frontier analysis; stochastic frontier estimation; prevention science; self-reported data; bias measurement; family interventions; USA; United States; Washington State; Oregon; participant demographics; gender; race; ethnicity; bias magnitude; bias changes; post-test bias; pre-test bias; programme effects; effect underestimates; metric shifts; behavioural research; healthcare research.

DOI: 10.1504/IJBHR.2011.043414

International Journal of Behavioural and Healthcare Research, 2011 Vol.2 No.4, pp.320 - 332

Published online: 30 Sep 2014 *

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