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An Item Response Theory Approach to Estimating Survey Mode Effects: Analysis of Data from a Randomized Mode Experiment

An Item Response Theory Approach to Estimating Survey Mode Effects: Analysis of Data from a... AbstractWhen a survey is offered in more than one mode of administration, the potential for differences in the probability of selecting a response category attributable to the survey administration mode may threaten the cross-mode exchangeability of responses or comparability of results. We demonstrate the utility of item response theory (IRT) in quantifying the presence of mode effects, providing insight into the nature of the effects and adjusting cross-mode results. Such IRT applications are of interest when the survey instrument informs an underlying latent trait. We present a Bayesian hierarchical IRT model that can accommodate multiple modes of survey administration and provide cluster-level parameter estimates of the latent trait when observed groupings of respondents are of interest. We illustrate the model with data from a randomized survey mode experiment in which responding subjects within each of forty-five evaluated institutions were randomly assigned to one of four response modes: mail, telephone, interactive voice response (IVR), and a mixed mode of mail with telephone follow-up. Results indicate instrument-wide survey mode effects that differ across ordinal response categories and the underutilization of an interior response category in certain modes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Survey Statistics and Methodology Oxford University Press

An Item Response Theory Approach to Estimating Survey Mode Effects: Analysis of Data from a Randomized Mode Experiment

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References (30)

Publisher
Oxford University Press
Copyright
© The Author 2017. Published by Oxford University Press on behalf of the American Association for Public Opinion Research. All rights reserved. For Permissions, please email: [email protected]
ISSN
2325-0984
eISSN
2325-0992
DOI
10.1093/jssam/smw033
Publisher site
See Article on Publisher Site

Abstract

AbstractWhen a survey is offered in more than one mode of administration, the potential for differences in the probability of selecting a response category attributable to the survey administration mode may threaten the cross-mode exchangeability of responses or comparability of results. We demonstrate the utility of item response theory (IRT) in quantifying the presence of mode effects, providing insight into the nature of the effects and adjusting cross-mode results. Such IRT applications are of interest when the survey instrument informs an underlying latent trait. We present a Bayesian hierarchical IRT model that can accommodate multiple modes of survey administration and provide cluster-level parameter estimates of the latent trait when observed groupings of respondents are of interest. We illustrate the model with data from a randomized survey mode experiment in which responding subjects within each of forty-five evaluated institutions were randomly assigned to one of four response modes: mail, telephone, interactive voice response (IVR), and a mixed mode of mail with telephone follow-up. Results indicate instrument-wide survey mode effects that differ across ordinal response categories and the underutilization of an interior response category in certain modes.

Journal

Journal of Survey Statistics and Methodology – Oxford University Press

Published: Jun 1, 2017

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