Measuring bias in self-reported data.
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.
School of Economic Sciences, Washington State University, P.O. Box 646210, Pullman, WA 99164-6210, USA.
Robert
R
Rosenman
School of Economic Sciences, Washington State University, P.O. Box 646210, Pullman, WA 99164-6210, USA vidhura@wsu.edu.
Vidhura
V
Tennekoon
Department of Human Development, Washington State University, 523 Johnson Tower, Pullman WA 99164, USA laurahill@wsu.edu.
Laura G
LG
Hill
SFE; prevention science; programme evaluation; response bias; response-shift bias; stochastic frontier analysis; stochastic frontier estimation