• Login
    View Item 
    •   Home
    • Office of Sponsored Research (OSR)
    • KAUST Funded Research
    • Publications Acknowledging KAUST Support
    • View Item
    •   Home
    • Office of Sponsored Research (OSR)
    • KAUST Funded Research
    • Publications Acknowledging KAUST Support
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of KAUSTCommunitiesIssue DateSubmit DateThis CollectionIssue DateSubmit Date

    My Account

    Login

    Quick Links

    Open Access PolicyORCID LibguideTheses and Dissertations LibguideSubmit an Item

    Statistics

    Display statistics

    Variable selection and estimation for longitudinal survey data

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Type
    Article
    Authors
    Wang, Li cc
    Wang, Suojin
    Wang, Guannan
    KAUST Grant Number
    KUS-CI-016-04
    Date
    2014-09
    Permanent link to this record
    http://hdl.handle.net/10754/600160
    
    Metadata
    Show full item record
    Abstract
    There is wide interest in studying longitudinal surveys where sample subjects are observed successively over time. Longitudinal surveys have been used in many areas today, for example, in the health and social sciences, to explore relationships or to identify significant variables in regression settings. This paper develops a general strategy for the model selection problem in longitudinal sample surveys. A survey weighted penalized estimating equation approach is proposed to select significant variables and estimate the coefficients simultaneously. The proposed estimators are design consistent and perform as well as the oracle procedure when the correct submodel was known. The estimating function bootstrap is applied to obtain the standard errors of the estimated parameters with good accuracy. A fast and efficient variable selection algorithm is developed to identify significant variables for complex longitudinal survey data. Simulated examples are illustrated to show the usefulness of the proposed methodology under various model settings and sampling designs. © 2014 Elsevier Inc.
    Citation
    Wang L, Wang S, Wang G (2014) Variable selection and estimation for longitudinal survey data. Journal of Multivariate Analysis 130: 409–424. Available: http://dx.doi.org/10.1016/j.jmva.2014.05.006.
    Sponsors
    The research of L. Wang was partially supported by NSF grants DMS-0905730, DMS-1106816, DMS-1309800 and the ASA/NSF/BLS research fellow program. The research of S. Wang was partially supported by Award Number KUS-CI-016-04, made by King Abdullah University of Science and Technology (KAUST). The views expressed in this paper are those of the authors and do not necessarily reflect the policies of the US Bureau of Labor Statistics.
    Publisher
    Elsevier BV
    Journal
    Journal of Multivariate Analysis
    DOI
    10.1016/j.jmva.2014.05.006
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.jmva.2014.05.006
    Scopus Count
    Collections
    Publications Acknowledging KAUST Support

    entitlement

     
    DSpace software copyright © 2002-2023  DuraSpace
    Quick Guide | Contact Us | KAUST University Library
    Open Repository is a service hosted by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items. For anonymous users the allowed maximum amount is 50 search results.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.