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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/54915
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/54915


    Title: 死亡壓縮與延壽之研究
    A study of mortality compression and prolonging life
    Authors: 李明峰
    Contributors: 余清祥
    李明峰
    Keywords: 死亡壓縮
    生存曲線矩形化
    死亡分佈
    數值優化
    壽命延長
    Mortality Compression
    Rectangularization of Survival Curve
    Distribution of age-at-death
    Prolonging Life
    Optimization
    Date: 2011
    Issue Date: 2012-10-30 14:21:37 (UTC+8)
    Abstract: 死亡壓縮(Mortality Compression)意指死亡年齡更集中,是最近廣受注意的研究議題,和生存曲線矩形化(Rectangularization)關係密切,以統計分佈的角度描述,則是死亡年齡會逐漸退化到某個特定年齡。換言之,如果死亡壓縮和壽命有上限兩者都成立,以統計術語而言,代表壽命的期望值有上限、變異數會收斂,可藉由死亡年齡分配探討壽命變化。
    本文希望以統計方法與資料品質等兩個面向探討死亡壓縮與延壽之間的關係。除了過去使用的無母數方法,如檢視各年度生命表上死亡分佈的最短區間(25%、50%及75%)與死亡人數最多的年齡(Modal Age)的變化,探討死亡壓縮與壽命是否有延長;另一方面,也將對死亡曲線作參數設定,觀察死亡年齡分佈的標準差變化。由於過往的研究多使用的生命表資料,本研究將比較使用生命表資料(死亡資料經過修勻)或原始死亡人數資料對結果的影響。
    本研究藉由電腦模擬比較各種估計標準差方法的差異,包括Kannisto (2000) 提出的SD(M+)法與本文考量的非線性極值法(Nonlinear-Maximization),衡量何者具有較小的均方誤差,並探討錯誤設定分配偵誤的敏感度;另外,本文可討論使用經過修勻的死亡率及原始死亡率對於估計結果的影響。除了電腦模擬,本研究也套入實際死亡資料(如臺灣、美國、…等國資料,資料來源:Human Mortality Database),檢視死亡壓縮是否存在。
    Mortality compression is one of the popular research issues in longevity risk. It means that the age-at-death would concentrate on a narrower range, and it is also related to the concept of rectangularization of survival curve. In terms of statistical distribution, mortality compression indicates that the age-at-death degenerates to a certain age, and it can be used to study changes of lifespan. If the lifespan has a limit, or mortality compression does exist, this suggests that the life expectancy has a limit and the variance of age-at-death would converge.
    In the study, we evaluate the mortality compression using the statistical methods and considering the issue of data quality. In addition to the nonparametric methods used in the previous studies, such as shortest confidence interval on the distribution of age-at-death and the modal age, we consider optimization methods for estimating the standard deviation of age-at-death distribution. In specific, we compare the SD(M+) proposed by Kannisto (2000) and the method of Nonlinear-Maximization, and check which method has a smaller MSE (Mean Squared Error). For the issue of data quality, we compare the estimation results of using mortality rates from life table data with those using the raw data.
    In addition to computer simulation, we consider the sensitivity analysis of age-at-death distribution, to evaluate the estimation method. Furthermore, based on the data from Human Mortality Database, we apply the method of Nonlinear-Maximization to life table data (i.e., graduated mortality rates) and raw data, and check if there are significant differences. The estimation results of empirical study are also used to evaluate if there is mortality compression and if there is a longevity limit.
    Reference: 中文部分
    王德睦與李大正 (2009)。臺灣的存活曲線矩型化與壽命延長。人口學刊,36,1-31。
    行政院經濟建設委員會人力規劃處 (2010)。2010年至2060年臺灣人口推計(編號:(99)033.805)。台北市:行政院經濟建設委員會。

    英文部分
    Cheung, K. S-L., J. Robine. J-C Tu, and G. Caselli. (2005). Three Dimensions of the Survival Curve: Horizontalization, Verticalization, and Longevity Extension. Demography 42(2): 243-258.
    Cheung, K. S-L., J. Robine. (2007). Increase in common longevity and the compressionof mortality: The case of Japan. Population Studies, 61:1, 85-97.
    Fries, J. (1980). Aging, Nature Death, and the Compression of Morbidity. The New England Journal of Medicine 303(3): 130-135.
    Kannisto, V. (2000). Measuring the Compression of Mortality. Demographic Research 3, Article6. (www.demographic-research.org/Volumes/Vol3/6).
    Kannisto, V. (2001). Mode and Dispersion of the Length of Life. Population: An English Selection 13(1): 159-172.
    Lexis, W. (1878). Sur la durée normale de la vie humaine et sur la théorie de la stabilité des rapports statistiques. Annales de Démographie Internationale 2(5): 447-460.
    Ouellette, N. and R. Bourbeau. (2011). Changes in the age-at-death distribution in four low mortality countries: A nonparametric approach. Demographic Research 25, Article 19. (www.demographic-research.org/Volumes/Vol25/19).
    Thatcher A.R., Cheung, K. S-L., S. Horiuchi, J. Robine. (2011). The compression of deaths above the mode. Demographic Research 22, Article 17. (www.demographic-research.org/Volumes/Vol22/17).
    Wilmoth, J. and S. Horiuchi. (1999). Rectangularization Revisited: Variability of Age at Death within Human Populations. Demography 36(4): 475-495.
    Yue, C.J. (2012).Mortality Compression and Longevity Limit, Contingencies, Jan/Feb, 42-45.
    WHO, http://www.who.int/en/
    Description: 碩士
    國立政治大學
    統計研究所
    99354014
    100
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0099354014
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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