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Modeling for Categorical Data and Handling Over-dispersion via Computer Intensive Methods

Research Project

Project/Area Number 12680319
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Statistical science
Research InstitutionOita University

Principal Investigator

OCHI Yoshimichi  Oita University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (60185618)

Co-Investigator(Kenkyū-buntansha) OBATA Tsuneshi  Oita University, Faculty of Engineering, Assistant Professor, 工学部, 助手 (00244153)
Project Period (FY) 2000 – 2002
Project Status Completed (Fiscal Year 2002)
Budget Amount *help
¥2,600,000 (Direct Cost: ¥2,600,000)
Fiscal Year 2002: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 2001: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2000: ¥1,500,000 (Direct Cost: ¥1,500,000)
Keywordsover-dispersion / bootstrap / jacknife / multinomial distribution / generalized estimating equations / distributed parallel precessing / ジャックナイフ法 / ブートストラップ法 / 最尤法 / 層別化逆回帰法 / 物理乱数生成器 / ロジスティックモデル
Research Abstract

Possibilities and performances of the use of computer intensive methods for handling over-dispersion are studied when we analyze effects of covariates on multi (including more than three) category response data. We set up a system to generate Dirichlet-multinominal random numbers based on the uniform random numbers given by a physical random number generator, using beta-binomial decomposition of the Dirichlet-multinominal distribution. Using this system, we carried out simulation studies for examining effects of handling over-dispersion regarding covariate effect evaluation in the categorical data analysis. Especially we focus on elucidating effectiveness of computer intensive methods such as bootstrap and jackknife methods, compared to the alternatives like multinomial maximum likelihood method (ML), Dirichlet-multinominal ML or generalized estimating equations (GEE) based on their moments up to 2nd order. The simulation results showed the computer intensive methods were comparable to the Dirichlet-multinominal ML, even in the case where the latter is the optimum for the study setting. Furthermore, it is indicated that the computer intensive methods are robust to the departure of the postulated models from the true structure.
Based on these simulation results, we applied above methods to some real data and we found that there was a case where the Dirichlet-multinominal ML failed to fit the data while the GEE and the computer intensive methods were able to fit the data successfully.
Since the calculations of the computational intensive methods themselves are costly, the simulation studies to evaluate their performances require substantial amount of computational burden. We therefore investigated efficient use of computational resources to ease this problem with simultaneous use of several computers via distributed parallel processing methods. This issue needs to be explored further.

Report

(4 results)
  • 2002 Annual Research Report   Final Research Report Summary
  • 2001 Annual Research Report
  • 2000 Annual Research Report
  • Research Products

    (10 results)

All Other

All Publications (10 results)

  • [Publications] Yoshimichi Ochi: "Adjusting over-dispersion in categorical data analysis with computer intensive methods"Proceedings-Abstracts of the XXIst International Biometric Conference, Special and contributed paper presentations. 90-91 (2002)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] 黒石 健太郎: "異機種環境下における分散計算処理と統計計算"大分大学工学部研究報告. 第47号. 15-20 (2003)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yoshimichi Ochi: "The Performance of Computer Intensive Methods for Over-dispersed Categorical Data"Journal of the Japanese Society of Computational Statistics. Vol.15, No.2(to appear). (2003)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yoshimichi Ochi: "Adjusting over-dispersion in categorical data analysis with computer intensive methods"Proceedings - Abstracts of the XXIst International Biometric Conference, Special and contributed paper presentaiona. 90-91 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Kentaro Kuroishi and Yoshimichi Ochi: "Distributed Processing and Statistical Computation under Heterogeneous Computational Environment"Reports of the Faculty of Engineering Oita University. No.47. 15-20 (2003)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yoshimichi Ochi: "The Performance of Computer Intensive Methods for Over-dispersed Categorical Data"Journal of the Japanese Society of Computational Statistics. Vol.15, No.2 (to appear).

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yoshimichi Ochi: "Adjusting over-dispersion in categorical data analysis with computer intensive methods"Proceedings-Abstracts of the XXIst International Biometric Conference, Special and contributed paper presentations. 90-91 (2002)

    • Related Report
      2002 Annual Research Report
  • [Publications] 黒石 健太郎: "異機種環境下における分散計算処理と統計計算"大分大学工学部研究報告. 第47号. 15-20 (2003)

    • Related Report
      2002 Annual Research Report
  • [Publications] Yoshimichi Ochi: "The Performance of Computer Intensive Methods for Over-dispersed Categorical Data"Journal of the Japanese Society of Computational Statistics. Vol.15,No.2(To appear). (2003)

    • Related Report
      2002 Annual Research Report
  • [Publications] Yoshimichi Ochi: "The performance of the computer intensive methods for over-dispersed categorical data"Proceedings of the International Conference on New Trends in Computational Statistics with Biomedical Applications. 305-312 (2001)

    • Related Report
      2001 Annual Research Report

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Published: 2000-04-01   Modified: 2016-04-21  

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