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The co-occurrence of self-observed norm-conforming behavior, reduction of zero observations and remaining measurement quality

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  • Johannes Landsheer

Abstract

Norm-violating behavior is characterized by clear social norms which prescribe the non-occurrence of that behavior. From the theoretical framework of Allport it is derived that specifically norm-conformation is consistent, while violating norms is expected to be inconsistent and more circumstantial. This is in contrast to test-theoretic approaches of delinquent behavior that assume that various norm-violating responses form a consistent answer pattern that is scalable and reliable. In this study we study the inter-correlations, scalability and reliability of norm-violating responses and their relation with the reduction of zero observations. In concordance with Allport’s view it is expected that different norm-violating self-report items have limited interrelatedness and are limited in scalability and reliability in the norm-violating sub-population. The NLSY98 self-report data show that a large majority of respondents (69 %) conform systematically to all ten different norms, while only nine percent admits more than two different violations. The results show that in subsamples of norm-violating respondents, the correlations between items become closer to zero, dependent on the amount of zero reduction. Furthermore, both Loevinger’s H coefficient of scalability and scale reliability become unsatisfactorily low, when 35 % or more strict norm-conforming subjects are removed. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Johannes Landsheer, 2014. "The co-occurrence of self-observed norm-conforming behavior, reduction of zero observations and remaining measurement quality," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2647-2656, September.
    • Handle: RePEc:spr:qualqt:v:48:y:2014:i:5:p:2647-2656
    DOI: 10.1007/s11135-013-9914-5
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    References listed on IDEAS

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    1. Souparno Ghosh & Alan E. Gelfand & Kai Zhu & James S. Clark, 2012. "The k-ZIG: Flexible Modeling for Zero-Inflated Counts," Biometrics, The International Biometric Society, vol. 68(3), pages 878-885, September.
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    3. L. Ark & Marcel Croon & Klaas Sijtsma, 2008. "Mokken Scale Analysis for Dichotomous Items Using Marginal Models," Psychometrika, Springer;The Psychometric Society, vol. 73(2), pages 183-208, June.
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