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Unweighted Sum of Squares Test for Proportions

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  • J. B. Copas

Abstract

The x2 test for proportions (or for independence in a 2 x m contingency table) requires that expected frequencies are not too small. An alternative to amalgamating low frequencies is to retain them but to give them less weight in the analysis. The resulting modified x2 test is also motivated by a likelihood argument based on a random effects model for the true proportions. The test works well in an example concerning error rates in computer records.

Suggested Citation

  • J. B. Copas, 1989. "Unweighted Sum of Squares Test for Proportions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 38(1), pages 71-80, March.
    • Handle: RePEc:bla:jorssc:v:38:y:1989:i:1:p:71-80
    DOI: 10.2307/2347682
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    Cited by:

    1. Xie, Xian-Jin & Pendergast, Jane & Clarke, William, 2008. "Increasing the power: A practical approach to goodness-of-fit test for logistic regression models with continuous predictors," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2703-2713, January.
    2. Andreas Blöchlinger & Markus Leippold, 2011. "A New Goodness-of-Fit Test for Event Forecasting and Its Application to Credit Defaults," Management Science, INFORMS, vol. 57(3), pages 487-505, March.
    3. Haegemans, Tom & Snoeck, Monique & Lemahieu, Wilfried, 2018. "Entering data correctly: An empirical evaluation of the theory of planned behaviour in the context of manual data acquisition," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 12-30.
    4. Francesco Bartolucci & Alessio Farcomeni, 2022. "A hidden Markov space–time model for mapping the dynamics of global access to food," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 246-266, January.
    5. Sturdivant, Rodney X. & Hosmer Jr., David W., 2007. "A smoothed residual based goodness-of-fit statistic for logistic hierarchical regression models," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3898-3912, May.

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