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Feeling Thermometers Versus 7-Point Scales

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  • DUANE F. ALWIN

    (University of Michigan)

Abstract

This study addresses the issue of the relation between the number of response categories used in survey questions and the quality of measurement. Several hypotheses, derived from relevant theory and research, are tested through a comparison between 7- and 11-category rating scales used in the 1978 Quality of Life Survey. One hypothesis derived from information theory, that rating scales with more response categories transmit a greater amount of information and are therefore inherently more precise in their measurement, is strongly supported. A second hypothesis, that questions with greater numbers of response categories are more vulnerable to systematic measurement errors or shared method variance, is rejected. This study supports the conclusion that questions with more categories are both more reliable and more valid.

Suggested Citation

  • Duane F. Alwin, 1997. "Feeling Thermometers Versus 7-Point Scales," Sociological Methods & Research, , vol. 25(3), pages 318-340, February.
    • Handle: RePEc:sae:somere:v:25:y:1997:i:3:p:318-340
    DOI: 10.1177/0049124197025003003
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    References listed on IDEAS

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    1. J. Ramsay, 1973. "The effect of number of categories in rating scales on precision of estimation of scale values," Psychometrika, Springer;The Psychometric Society, vol. 38(4), pages 513-532, December.
    2. 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.
    3. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
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    Cited by:

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    2. Helbling, Marc & Traunmüller, Richard, 2020. "What is Islamophobia? Disentangling Citizens’ Feelings Toward Ethnicity, Religion and Religiosity Using a Survey Experiment," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 50(3), pages 811-828.
    3. Lin, Lily & Hoegg, JoAndrea & Aquino, Karl, 2018. "When Beauty Backfires: The Effects of Server Attractiveness on Consumer Taste Perceptions," Journal of Retailing, Elsevier, vol. 94(3), pages 296-311.
    4. Martin Kroh, 2006. "An Experimental Evaluation of Popular Well-Being Measures," Discussion Papers of DIW Berlin 546, DIW Berlin, German Institute for Economic Research.
    5. Wittlin, Natalie M. & Dovidio, John F. & Burke, Sara E. & Przedworski, Julia M. & Herrin, Jeph & Dyrbye, Liselotte & Onyeador, Ivuoma N. & Phelan, Sean M. & van Ryn, Michelle, 2019. "Contact and role modeling predict bias against lesbian and gay individuals among early-career physicians: A longitudinal study," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
    6. Alice Audrezet & Béatrice Parguel, 2017. "Designing measurement tools to improve fluency and certainty: The case of online customer satisfaction evaluation," Post-Print hal-01821838, HAL.
    7. Kroh, Martin, 2007. "Measuring Left-Right Political Orientation: The Choice of Response Format," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 71(2), pages 204-220.
    8. Anna DeCastellarnau, 2018. "A classification of response scale characteristics that affect data quality: a literature review," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1523-1559, July.

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