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January 1, 1984Public Opinion Quarterly416 citations

Construct Validity and Error Components of Survey Measures: A Structural Modeling Approach

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FAFrank M. Andrews

Key Points

  • The aim is to evaluate the construct validity and analyze the error components within survey measures.
  • Applied structural modeling to assess the validity of survey instruments.
  • Incorporated feedback and methodological insights from various contributors.
  • Analyzed data from multiple surveys conducted by notable researchers.
  • Findings indicate that structural modeling enhances understanding of validity and error components.
  • Identified specific areas where survey measures may misrepresent constructs or introduce biases.
  • Demonstrated that collaboration with methodological experts significantly improves survey design.

Abstract

Journal Article Construct Validity and Error Components of Survey Measures: A Structural Modeling Approach Get access FRANK M. ANDREWS FRANK M. ANDREWS Frank M. Andrews is Program Director in the Survey Research Center and Professor of Psychology and of Population Planning at the University of Michigan. Gerald A. Cole and Mary Grace Moore made numerous and substantial contributions to the work reported here. The author is grateful to David Bowers, Angus Campbell, Charles Cannell, Philip Converse, Richard Curtin, Daniel Denison, and Robert Groves for allowing us to include methodological supplements in some of their surveys. Earlier versions of this paper were presented at the 1980 Annual Meeting of the American Psychological Association, at the 1982 Annual Meeting of the American Association for Public Opinion Research, and at the 1982 Conference on Health Survey Research Methods. This research was supported by grant #SOC78-07676 from the National Science Foundation. Search for other works by this author on: Oxford Academic Google Scholar Public Opinion Quarterly, Volume 48, Issue 2, SUMMER 1984, Pages 409–442, https://doi.org/10.1086/268840 Published: 01 January 1984

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Frank M. Andrews (1984) studied this question.

synapsesocial.com/papers/6a09b3bf4db79685905178c6https://doi.org/10.1086/268840
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