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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41459

    Title: Residuals analysis of the generalized linear models for longitudinal data
    Authors: Chang, Y. C.
    Contributors: 淡江大學數學學系
    Keywords: article;biostatistics;clinical study;correlation function;longitudinal study;medical research;statistical analysis;statistical model;Adult;Aged;Aged, 80 and over;Diabetic Retinopathy;Female;Humans;Linear Models;Longitudinal Studies;Male;Meningeal Neoplasms;Meningioma;Middle Aged;Models, Biological;Mydriasis;Mydriatics;Pupil;Radiosurgery
    Date: 2000-05-01
    Issue Date: 2013-08-08 14:44:11 (UTC+8)
    Publisher: Chichester: John Wiley & Sons Ltd.
    Abstract: The generalized estimation equation (GEE) method, one of the generalized linear models for longitudinal data, has been used widely in medical research. However, the related sensitivity analysis problem has not been explored intensively. One of the possible reasons for this was due to the correlated structure within the same subject. We showed that the conventional residuals plots for model diagnosis in longitudinal data could mislead a researcher into trusting the fitted model. A non-parametric method, named the Wald-Wolfowitz run test, was proposed to check the residuals plots both quantitatively and graphically. The rationale proposed in this paper is well illustrated with two real clinical studies in Taiwan.
    Relation: Statistics in Medicine 19(10), pp.1277-1293
    DOI: 10.1002/(SICI)1097-0258(20000530)19:103.0.CO;2-S
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

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