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Research on Survey Quality

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  • DUANE F. ALWIN

    (University of Michigan)

Abstract

This article provides a review of recent research on the quality of survey data and serves as an introduction to this special issue of SMR. The article reviews standard statistical treatments of survey errors and discusses the importance of developing population models for measurement errors. A model is presented which nests measurement errors within other nonmeasurement survey errors—errors of coverage, sampling, and nonresponse. Promising new developments in research on survey measurement are reviewed and evaluated—applications of rational choice theories of response behavior, applications of cognitive theories of judgment and information processing, and experiments in the meaning of questions. The article concludes with a brief summary of the contributions included in this special issue of SMR.

Suggested Citation

  • Duane F. Alwin, 1991. "Research on Survey Quality," Sociological Methods & Research, , vol. 20(1), pages 3-29, August.
    • Handle: RePEc:sae:somere:v:20:y:1991:i:1:p:3-29
    DOI: 10.1177/0049124191020001001
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    References listed on IDEAS

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    1. Duane Alwin, 1989. "Problems in the estimation and interpretation of the reliability of survey data," Quality & Quantity: International Journal of Methodology, Springer, vol. 23(3), pages 277-331, September.
    2. Achen, Christopher H., 1975. "Mass Political Attitudes and the Survey Response," American Political Science Review, Cambridge University Press, vol. 69(4), pages 1218-1231, December.
    3. Converse, Philip E. & Markus, Gregory B., 1979. "Plus ça change…: The New CPS Election Study Panel," American Political Science Review, Cambridge University Press, vol. 73(1), pages 32-49, March.
    4. Erikson, Robert S., 1979. "The SRC Panel Data and Mass Political Attitudes," British Journal of Political Science, Cambridge University Press, vol. 9(1), pages 89-114, January.
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    Cited by:

    1. Bruce D. Meyer & Nikolas Mittag, 2019. "An Empirical Total Survey Error Decomposition Using Data Combination," NBER Working Papers 25737, National Bureau of Economic Research, Inc.

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