• About
    • Login
    View Item 
    •   Institutional Repository Home
    • Electronic Theses and Dissertations
    • Electronic Theses and Dissertations
    • View Item
    •   Institutional Repository Home
    • Electronic Theses and Dissertations
    • Electronic Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Institutional RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDepartmentThis CollectionBy Issue DateAuthorsTitlesSubjectsDepartment

    My Account

    LoginRegister

    Identifying Patterns of Abridged Life Table Elements

    Curtis, Alice Elizabeth
    : https://etd.library.vanderbilt.edu/etd-06212017-081429
    http://hdl.handle.net/1803/12656
    : 2017-06-26

    Abstract

    The CDC Wide-ranging ONline Data for Epidemiologic Research (CDC WONDER) makes many health-related datasets available to the public health community through web applications. One such available dataset is The Multiple Cause of Death data which displays county-level national mortality and population data. One of the main issues with this particular dataset is that the death counts within the age groups can be very small or equal to zero for various counties which can cause the conditional probability of death to be small or even zero. This issue causes the estimates for life expectancy within the abridged life table to be unreliable. This research utilizes the data provided by CDC WONDER, distance measures (Euclidean and discrete Hellinger distances), Metric Multidimensional Scaling, and Partitioning Around Medoids to identify patterns of life table elements among the "stable" counties within the dataset. The identification of these patterns is then used to classify the patterns which the "unstable" counties fall into. Future work will aim at borrowing from the "stable" counties, geographic and demographic information, which the "unstable" counties most closely resemble in order to better predict their life table elements, particularly life expectancies.
    Show full item record

    Files in this item

    Icon
    Name:
    Curtis.pdf
    Size:
    2.682Mb
    Format:
    PDF
    View/Open

    This item appears in the following collection(s):

    • Electronic Theses and Dissertations

    Connect with Vanderbilt Libraries

    Your Vanderbilt

    • Alumni
    • Current Students
    • Faculty & Staff
    • International Students
    • Media
    • Parents & Family
    • Prospective Students
    • Researchers
    • Sports Fans
    • Visitors & Neighbors

    Support the Jean and Alexander Heard Libraries

    Support the Library...Give Now

    Gifts to the Libraries support the learning and research needs of the entire Vanderbilt community. Learn more about giving to the Libraries.

    Become a Friend of the Libraries

    Quick Links

    • Hours
    • About
    • Employment
    • Staff Directory
    • Accessibility Services
    • Contact
    • Vanderbilt Home
    • Privacy Policy