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Assessing cumulative logit models via a score test in random effect models

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  • Kuo-Chin Lin

Abstract

The purpose of this article is to develop a goodness-of-fit test based on score test statistics for cumulative logit models with extra variation of random effects. Two main theorems for the proposed score test statistics are derived. In simulation studies, the powers of the proposed tests are discussed and the power curve against a variety of dispersion parameters and bandwidths is depicted. The proposed method is illustrated by an ordinal data set from Mosteller and Tukey [23].

Suggested Citation

  • Kuo-Chin Lin, 2011. "Assessing cumulative logit models via a score test in random effect models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 247-259, September.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:2:p:247-259
    DOI: 10.1080/02664760903406421
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    References listed on IDEAS

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    1. Gautam, Shiva & Kimeldorf, George & Sampson, Allan R., 1996. "Optimized scorings for ordinal data for the general linear model," Statistics & Probability Letters, Elsevier, vol. 27(3), pages 231-239, April.
    2. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    3. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
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