Web Survey Bibliography
Title Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities’ Impact on Patterns of Bias
Author Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
Source Public Opinion Quarterly (POQ); 81, 2, pp. 401-421
Year 2017
Database Oxford Journals
Access date 24.08.2017
Abstract
In this study, survey nonresponse is researcher specified
and data simulated to evaluate its impact on error and bias in attitudinal
ratings. We accomplish this by scaling densities of (non)response
probabilities to a survey’s item metric and using these now conditional
probabilities to sample from known attitudinal distributions. The illustrative
context we choose for our simulations is intra-organizational
surveying (within which attitudes toward constructs such as employee
engagement, job satisfaction, or organizational climate are commonly
polled), although the results and implications extend to any survey with
metrically consonant item response scales. The simulations identify
population and response pattern combinations that are either susceptible
or relatively immune to bias. We then demonstrate how this procedure
can be inverted and applied as a bias correction technique for dealing
with nonresponse. This inversion is the only existing sample corrective
procedure (known within the literature) that can be applied with no requisite
knowledge of target population parameters, instead requiring an
estimation of patterns of nonresponse.
and data simulated to evaluate its impact on error and bias in attitudinal
ratings. We accomplish this by scaling densities of (non)response
probabilities to a survey’s item metric and using these now conditional
probabilities to sample from known attitudinal distributions. The illustrative
context we choose for our simulations is intra-organizational
surveying (within which attitudes toward constructs such as employee
engagement, job satisfaction, or organizational climate are commonly
polled), although the results and implications extend to any survey with
metrically consonant item response scales. The simulations identify
population and response pattern combinations that are either susceptible
or relatively immune to bias. We then demonstrate how this procedure
can be inverted and applied as a bias correction technique for dealing
with nonresponse. This inversion is the only existing sample corrective
procedure (known within the literature) that can be applied with no requisite
knowledge of target population parameters, instead requiring an
estimation of patterns of nonresponse.
Access/Direct link Journal Homepage (abstract) / (full text)
Year of publication2017
Bibliographic typeJournal article
Web survey bibliography (367)
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- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
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- A test of sample matching using a pseudo-web sample; 2017; Chatrchi, G., Gambino, J.
- A Partially Successful Attempt to Integrate a Web-Recruited Cohort into an Address-Based Sample; 2017; Kott, P. S., Farrelly, M., Kamyab, K.
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- Data chunking for mobile web: effects on data quality; 2017; Lugtig, P. J.; Toepoel, V.
- Comparing data quality and cost from three modes of on-board transit surveys ; 2017; Agrawal, A. W.; Granger-Bevan, S.; W.; Newmark, G. L.; Nixon, H.
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- Dynamic Question Ordering in Online Surveys; 2016; Early, K.; Mankoff, J.; Fienberg, S. E.
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- Targeted Appeals for Participation in Letters to Panel Survey Members; 2016; Lynn, P.
- Can we assess representativeness of cross-national surveys using the education variable?; 2016; Ortmanns, V.; Schneider, S.
- Methodological Aspects of Central Left-Right Scale Placement in a Cross-national Perspective; 2016; Scholz, E.; Zuell, C.
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- Comparison of Face-to-Face and Web Surveys on the Topic of Homosexual Rights; 2016; Liu, M.; Wang, Yic.
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- Web-Based Statistical Sampling and Analysis; 2016; Quinn, A.; Larson, K.