American Journal of Theoretical and Applied Statistics

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Estimating the Fisher’s Scoring Matrix Formula from Logistic Model

Received: 21 October 2013    Accepted:     Published: 20 November 2013
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Abstract

This paper proposes a matrix approach to estimating parameters of logistic regression with a view to estimating the effects of risk factors of gestational diabetic mellitus (GDM). The proposed method of maximum likelihood estimation (MLE) unlike other methods of estimating parameters of non-linear regression is simpler and convergence of parameters is quicker. The odds ratio obtained from the logistic regression were used to interpret the effects of these risk factors on GDM where obesity and F.H as risk factors, were positively associated with GDM. The proposed method was seen to compare favorably with other known methods.

DOI 10.11648/j.ajtas.20130206.19
Published in American Journal of Theoretical and Applied Statistics (Volume 2, Issue 6, November 2013)
Page(s) 221-227
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

GDM, Logistic Regression, Dichotomous, Fisher Scoring, Newton-Raphson, Risk factors

References
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[18] Miyakoshi K, Tanaka M, Ueno K, Uehara K, Ishimoto H, Yoshimura Y. Cutoff value of 1 h, 50 g glucose challenge test for screening of gestational diabetes mellitus in a Japanese population. Diabetes Res Clin Pract 2003; 60: 63-7.
[19] Pepe, M. S.(2003). The Statistical Evaluation of Medical Tests for Classification and Prediction, Oxford University Press, New York, NY, USA.
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Author Information
  • Department of Industrial Mathematics and Applied Statistics, Ebonyi State University Abakaliki, Nigeria

  • Department of Applied Statistics, Nnamdi Azikiwe University, Awka Nigeria

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    Okeh UM, Oyeka I. C. A. (2013). Estimating the Fisher’s Scoring Matrix Formula from Logistic Model. American Journal of Theoretical and Applied Statistics, 2(6), 221-227. https://doi.org/10.11648/j.ajtas.20130206.19

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    ACS Style

    Okeh UM; Oyeka I. C. A. Estimating the Fisher’s Scoring Matrix Formula from Logistic Model. Am. J. Theor. Appl. Stat. 2013, 2(6), 221-227. doi: 10.11648/j.ajtas.20130206.19

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    AMA Style

    Okeh UM, Oyeka I. C. A. Estimating the Fisher’s Scoring Matrix Formula from Logistic Model. Am J Theor Appl Stat. 2013;2(6):221-227. doi: 10.11648/j.ajtas.20130206.19

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  • @article{10.11648/j.ajtas.20130206.19,
      author = {Okeh UM and Oyeka I. C. A.},
      title = {Estimating the Fisher’s Scoring Matrix Formula from Logistic Model},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {2},
      number = {6},
      pages = {221-227},
      doi = {10.11648/j.ajtas.20130206.19},
      url = {https://doi.org/10.11648/j.ajtas.20130206.19},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajtas.20130206.19},
      abstract = {This paper proposes a matrix approach to estimating parameters of logistic regression with a view to estimating the effects of risk factors of gestational diabetic mellitus (GDM). The proposed method of maximum likelihood estimation (MLE) unlike other methods of estimating parameters of non-linear regression is simpler and convergence of parameters is quicker. The odds ratio obtained from the logistic regression were used to interpret the effects of these risk factors on GDM where obesity and F.H as risk factors, were positively associated with GDM. The proposed method was seen to compare favorably with other known methods.},
     year = {2013}
    }
    

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    AB  - This paper proposes a matrix approach to estimating parameters of logistic regression with a view to estimating the effects of risk factors of gestational diabetic mellitus (GDM). The proposed method of maximum likelihood estimation (MLE) unlike other methods of estimating parameters of non-linear regression is simpler and convergence of parameters is quicker. The odds ratio obtained from the logistic regression were used to interpret the effects of these risk factors on GDM where obesity and F.H as risk factors, were positively associated with GDM. The proposed method was seen to compare favorably with other known methods.
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