Accepted manuscript
Measuring bias in self-reported data
International journal of behavioural & healthcare research, Vol.2(4), pp.320-332
01/01/2011
Handle:
https://hdl.handle.net/2376/112697
PMCID: PMC4224297
PMID: 25383095
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.
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Details
- Title
- Measuring bias in self-reported data
- Creators
- Robert Rosenman - School of Economic Sciences, Washington State University, P.O. Box 646210, Pullman, WA 99164-6210, USAVidhura Tennekoon - School of Economic Sciences, Washington State University, P.O. Box 646210, Pullman, WA 99164-6210, USALaura G Hill - Department of Human Development, Washington State University, 523 Johnson Tower, Pullman WA 99164, USA
- Publication Details
- International journal of behavioural & healthcare research, Vol.2(4), pp.320-332
- Academic Unit
- Office of the Provost; Community Health
- Publisher
- Inderscience Publishers Ltd
- Identifiers
- 99900548283001842
- Language
- English
- Resource Type
- Accepted manuscript