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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/106940

    Title: The extensively corrected score for measurement error models
    Authors: Yih-Huei Huang , Chi-Chung Wen, Yu-Hua Hsu
    Keywords: conditional score;corrected score;extensively corrected score;generalized linear models;measurement errors
    Date: 2015/12
    Issue Date: 2016-08-15
    Abstract: In measurement error problems, two major and consistent estimation methods are the conditional score and the corrected score. They are functional methods that require no parametric assumptions on mismeasured covariates. The conditional score requires that a suitable sufficient statistic for the mismeasured covariate can be found, while the corrected score requires that the object score function can be estimated without bias. These assumptions limit their ranges of applications. The extensively corrected score proposed here is an extension of the corrected score. It yields consistent estimations in many cases when neither the conditional score nor the corrected score is feasible. We demonstrate its constructions in generalized linear models and the Cox proportional hazards model, assess its performances by simulation studies and illustrate its implementations by two real examples.
    Relation: Scandinavian Journal of Statistics 42(4), pp.911–924
    DOI: 10.1111/sjos.12143
    Appears in Collections:[數學學系暨研究所] 期刊論文

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