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Measuring bias in self-reported data
Open accessAbstract
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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“First, the study used a self-report survey with its well-known potential method biases ranging from a misunderstanding of measures' purposes to social-desirability bias (Rosenman, Tennekoon, & Hill, 2011).”
From Adolescents’ Body Shame and Social Networking Sites: The Mediating Effect of Body Image Control in Photos (2020) · cites this paper as Rosenman, Tennekoon, & Hill, 2011
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“…potential for recalibration of self-rating bias as a function of material or skills learned in an intervention has long been a concern to programme evaluators as it may result in underestimates of programme effectiveness (Howard and Dailey, 1979; Norman, 2003; Pratt et al., 2000; Sprangers, 1989).”
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“Based on previous literature (Howard and Dailey, 1979), we hypothesised that the one-sided errors (response bias) would be downward, and preliminary analysis supported that hypothesis.3 Additional preliminary analysis of which variables to include among zi (including a model using all the…”
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Darviri, C., Zigkiri, E., Simos, D. S., Charalampopoulou, M., Kokka, I., Vlachakis, D., Bacopoulou, F., & Chrousos, G. P. (2023) · Advances in experimental medicine and biology · doi:10.1007/978-3-031-31986-0_6 · Cited by 4
Terkamo‐Moisio, A., Peltonen, L., Kaakinen, P., Palonen, M., Vaartio‐Rajalin, H., Fagerström, L., Kaunonen, M., Leino‐Kilpi, H., & Häggman‐Laitila, A. (2023) · The Journal of Continuing Education in Nursing · doi:10.3928/00220124-20230829-04 · Cited by 3
Characteristics of Self-Rated Oral Health among Syrian Refugee Parents in Ontario
Alzaghoul, A. F., Rahimpoor-Marnani, P., Yunis, K. A., Alamgir, A., Alghalyini, B., & Tamim, H. (2023) · International Journal of Dentistry · doi:10.1155/2023/4136520 · Cited by 3
Metadata
- Authors
- Rosenman, R., Tennekoon, V., & Hill, L. G.
- Affiliations
- Washington State University (US)
- Corresponding author
- Rosenman, Robert
- Venue
- International Journal of Behavioural and Healthcare Research
- Publisher
- Inderscience Publishers
- Published
- 2011
- Volume
- 2
- Issue
- 4
- Pages
- 320
- ISSN
- 1755-3539 (ISSN-L)
- 1755-3547
- PMC
- PMC4224297
- OpenAlex
- W2078684842
- Cited by
- 1,050
- References
- 15
- Citations by year
- 2026: 131 · 2025: 200 · 2024: 126 · 2023: 123 · 2022: 147 · 2021: 121 · 2020: 104 · 2019: 73 · 2018: 16 · 2017: 3 · 2015: 1 · 2014: 2 · 2013: 1
- FWCI
- 1.30
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- International Journal of Behavioural and Healthcare Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Drug Abuse (R21DA025139, R21DA019758)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- response bias, self-reported data, response-shift bias, family intervention, gender differences, race and ethnicity, measurement bias, program evaluation
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