Literature DB >> 25383095

Measuring bias in self-reported data.

Robert Rosenman1, Vidhura Tennekoon2, Laura G Hill3.   

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.

Entities:  

Keywords:  SFE; prevention science; programme evaluation; response bias; response-shift bias; stochastic frontier analysis; stochastic frontier estimation

Year:  2011        PMID: 25383095      PMCID: PMC4224297          DOI: 10.1504/IJBHR.2011.043414

Source DB:  PubMed          Journal:  Int J Behav Healthc Res        ISSN: 1755-3539


  5 in total

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5.  An application of structural equation modeling to detect response shifts and true change in quality of life data from cancer patients undergoing invasive surgery.

Authors:  Frans J Oort; Mechteld R M Visser; Mirjam A G Sprangers
Journal:  Qual Life Res       Date:  2005-04       Impact factor: 4.147

  5 in total
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