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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/36928
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/36928


    Title: APC模型估計方法的模擬與實證研究
    Simulation and empirical comparisons of estimation methods for the APC model
    Authors: 歐長潤
    Ou, Chang Jun
    Contributors: 余清祥
    Yue, Jack C.
    歐長潤
    Ou, Chang Jun
    Keywords: APC模型
    廣義線性模式
    本質估計量
    死亡率模型
    電腦模擬
    Age–Period–Cohort Model
    Generalized Linear Models
    Intrinsic Estimator
    Mortality Rates Models
    Simulation
    Date: 2008
    Issue Date: 2009-09-18 20:10:50 (UTC+8)
    Abstract: 20世紀以來,因為衛生醫療等因素的進步,各年齡死亡率均大幅下降,使得平均壽命大幅延長。壽命延長的效果近年逐漸顯現,其中的人口老化及其相關議題較受重視,因為人口老化已徹底改變國人的生活規劃,死亡率是否會繼續下降遂成為熱門的研究課題。描述死亡率變化的模型很多,近代發展的Age–Period–Cohort模型(簡稱APC模型),同時考慮年齡、年代與世代三個解釋變數,是近年廣受青睞的模型之一。這個模型將死亡率分成年齡、年代與世代三個效應,常用於流行病學領域,探討疾病、死亡率是否與年齡、年代、世代三者有關,但一般僅作為資料的大致描述,本研究將評估APC模型分析死亡率的可能性。
    APC模型最大的問題在於不可甄別(Non–identification),即年齡、年代與世代三個變數存有共線性的問題,眾多的估計APC模型參數方法因應甄別問題而生。本研究預計比較七種較常見的APC模型估計方法,包括本質估計量(IE)、限制的廣義線性模型(cglim_age、cglim_period與cglim_cohort)、序列法ACP、序列法APC與自我迴歸模型(AR),以確定哪一種估計方法較為穩定,評估包括電腦模擬與實證分析兩部份。
    電腦模擬部份比較各估計方法,衡量何者有較小的年齡別死亡率及APC參數的估計誤差;實證分析則考慮交叉分析,尋找用於死亡率預測的最佳估計方法。另外,也將以蒙地卡羅檢驗APC的模型假設,以確定這個模型的可行性。初步研究發現,以台灣死亡資料做為實證,本研究考量的估計方法在估計年齡別死亡率大致相當,只是在年齡–年代–世代這三者有不同的詮釋,且模型假設並非很符合。交叉分析上,Lee–Cater模型及其延展模型相對於APC模型有較小的預測誤差,整體顯示Lee–Cater 模型較佳。
    Since the beginning of the 20th century, the human beings have been experiencing longer life expectancy and lower mortality rates, which can attributed to constant improvements of factors such as medical technology, economics, and environment. The prolonging life expectancy has dramatically changed the life planning and life style after the retirement. The change would be even more severe if the mortality rates have larger reduction, and thus the study of mortality become popular in recent years. Many methods were proposed to describe the change of mortality rates. Among all methods, the Age-Period-Cohort model (APC) is a popular method used in epidemiology to discuss the relation between diseases, mortality rate, age, period and cohort.
    Non-identification (i.e. collinearity) is a serious problem for APC model, and many methods used in the procedure included estimation of parameter. In the first part of this paper, we use simulation compare and evaluate popular estimation methods of APC model, such as Intrinsic Estimator (IE), constrained of age, period and cohort in the Generalized Linear Model (c–glim), sequential method, and Auto-regression (AR) Model. The simulation methods considered include Monte-Carlo and cross validation. In addition, the morality data in Taiwan (Data sources: Ministry of Interior), are used to demonstrate the validity and model assumption of these methods. In the second part of this paper, we also apply similar research method to the Lee-Carter model and compare it to the APC model. We found Lee–Carter model have smaller prediction errors than APC models in the cross–validation.
    Reference: 中文部分
    王郁萍(2006)。台灣地區死亡率APC模型之研究,國立政治大學統計研究所碩士論文。
    李文宗(1994)。年齡--年代—世代分析方法新探,國立臺灣大學公共衛生學研究所博士論文。
    郭雅雅(2005)。台灣地區服務業就業趨勢之年齡、年代及世代分析,國立政治大學統計研究所碩士論文。
    郭雅婷(2007)。台灣地區女性勞動參與在生命歷程之變異-APC模型之應用,國立政治大學社會學研究所。
    黃意萍、余清祥(2002)。台灣地區生育率模式的推估研究,人口學刊,25:145–171。
    曾奕翔(2002)。台灣地區死亡率推估的實證方法之研究與相關年金問題之探討,國立政治大學統計研究所碩士論文。
    余清祥、藍銘偉(2003)。台灣地區生育率模型之研究,人口學刊,27:105–131。
    英文部分
    Bell W R. (1997) Comparing and assessing time series methods for forecasting age–specific fertility and mortality rates. Journal of Official Statistics, 13(3): 279–303.
    Cairns, A. J. G., Blake, D., and Dowd, K. (2009) A quantitative comparison of stochastic mortality models using data from England & Wales and the United States, North American Actuarial Journal. 13(1): 1–35.
    Carstensen, B and Keiding, N. (2004) Age–period–cohort models: Statistical inference in the lexis diagram. Lecture notes, Department of Biostatistics, University of Copenhagen, http://www.biostat.ku.dk/~bxc/APC/notes.pdf
    Carstensen, B and Keiding, N. (2005) Demography and epidemiology: Age–period–cohort models in the computer age, Department of Biostatistics, University of Copenhagen, http://www.pubhealth.ku.dk/bs/publikationer/rr-06-1.pdf.
    Carter, L.R., and Lee, R.D. (1992) Modeling and forecasting US sex differentials in Mortality. International Journal of Forecasting, 8:393–411.
    Christensen, R. (2002) Plane Answers to Complex Questions: The Theory of Linear Models, third edition, Springer–Verlag, New York.
    Clayton, D. and Schifflers, E. (1987) Models for temporal variation in cancer rates I: Age–period and age–cohort models. Statistics in Medicine, 6:449–467.
    Clayton, D. and Schifflers, E. (1987) Models for temporal variation in cancer rates II: Age–period–cohort models. Statistics in Medicine, 6:469–481.
    Frost, W.H.(1939) The selection of mortality from tuberculosis in successive decades, American Journal of Hygiene (Section Age), 30:91–96.
    Fu,W.J. (2000) Ridge Estimator in Singular Design with Application to Age–Period–Cohort Analysis of Disease Rates. Communications in Statistics-Theory and Method, 29:263–278.
    Fu, W.J. Hall, P. and Rohan, T. (2004) Age–period–cohort analysis: structure of estimators, estimability, sensitivity and asymptotics, Technical report, Department of Epidemiology, Michigan State University.
    Fu, W.J. and Hall, P. (2006) Asymptotic Properties of Estimators in Age-Period-Cohort Analysis. Statistics and Probability Letters, 76:1925–1929.
    Fu,W.J. (2007). A Smoothing cohort model in Age–Period–Cohort Analysis with Applications to Homicide Arrest Rates and Lung Cancer Mortality Rates, http://www.msu.edu/~fuw/apc/apcsmthFinal.pdf
    Gompertz, B. (1825) On the nature of the function expressive of the law of human mortality and on a mew mode of determining life contingentcies. Philosophical Transactions of the Royal Society of London, 115:513–585.
    Hastie, T. and Tibshirani, R. (1990) Generalized Additive Models, Chapman and Hall, New York.
    Heligman, L. M. A. and Pollard, J. H. (1980) The age pattern of mortality. Journal of the Institute of Actuaries, 107(1): 49–82.
    Holford TR. (1983) The estimation of age, period and cohort effects for vital rates. Biometrics, 39:311–324.
    Holford TR. (2006) Approaches to fitting age–period–cohort models with unequal intervals. Statistics in Medicine, 25:977–993.
    Kupper, L.L., Janis, J.M., Karmous, A. and Greenberg, B.G. (1985) Statistical age- period-cohort analysis: a review and critique. Journal of Chronic. Diseases, 38: 811–830.
    Lee, W.C. and Lin, R.C. (1996) Autoregressive age period cohort models. Statistics in Medicine, 15:273–281.
    Lee, R. D. and Carter L. R. (1992) Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87:659–675.
    O’Bren, R.M. (2000) Age Period Cohort Characteristic Models. Social Science Research, 29, 123–139.
    Osmond, C. and Gardner, M.J. (1982) Age, period and cohort models applied to cancer mortality rates. Statistics in Medicine, 1:245–259.
    Renshaw, A. E., and Haberman, S. (2006) A cohort–based extension to the Lee-Carter model for mortality reduction factors. Insurance: Mathematics and Economics, 38: 556–570.
    Robertson, C. Gandini, S. and Boyle, P. (1999) Age–Period–Cohort Models: A Comparative Study of Available Methodologies. Journal of Clinical Epidemiology, 52(6): 569–583.
    Robertson , C. and Boyle, P. (1999) Age–peiod–cohort models of chronic disease rates I: modeling approaches. Statistics in Medicine, 17:1305–1323.
    Robertson , C. and Boyle, P. (1999) Age–peiod–cohort models of chronic disease rates II: graphical approaches, Statistics in Medicine. 17:1325–1340.
    Ryder, N. B. (1965) The cohort as a concept in the study of social change. American Sociological Review, 30:843–861.
    Smith, H. (2008) Advances in Age–Period–Cohort Analysis, Sociological Methods and Research 36: 287–296.
    Tarone RE, Chu KC. (1992) Implications of birth cohort patterns in interpreting trends in breast cancer rates. Journal of National Cancer Institute, 84:1402–1410.
    Wilmoth, J. R. (1993) Computational Methods for Fitting and Extrapolating the Lee–Carter Model of Mortality Change. Technical report, Department of Demography, University of California, Berkeley.
    Yang, Y., Fu, W.J. and Land, K. (2004) A methodological comparison of age–period–cohort models: the intrinsic estimator and conventional generalized linear models. Sociological Methodology, 34:75–110.
    Yang, Y., Sam SW and Land, K. (2007) A Simulation Study of the Intrinsic Estimator
    for Age–Period–Cohort Analysis, http://paa2008.princeton.edu/download.aspx?submissionId=80691
    Yang, Y. and Land, K. (2008) Age–Period–Cohort Analysis of Repeated Cross-Section Surveys: Fixed or Random Effects? Sociological Methods and Research 36: 297–326.
    Yang, Y. (2008) Trends in U.S. Adult Chronic Disease Mortality, 1960–1999: Age, Period, and Cohort Variations. Demography 45: 387–416.
    Yang, Y., Sam SW, Fu, W.J. and Land, K. (2008) The Intrinsic Estimator for Age–Period–Cohort Analysis: What It is and How to Use it? American Journal of Sociology 113: 1697–1736.
    Description: 碩士
    國立政治大學
    統計研究所
    96354007
    97
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0096354007
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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