A Stepwise Logistic Regression Analysis: An application toward Poultry Farm Data in Johor

  • Authors

    • Siti Afiqah Muhamad Jamil
    • Mohd Asrul Affendi Abdullah
    • Kek Sie Long
    • Nur Fazilla Mohd Jupri
    • Mustafa Mamat
    2018-08-17
    https://doi.org/10.14419/ijet.v7i3.28.20968
  • Stepwise Logistic Regression Analysis, SPSS software, Akaike Information Criterion (AIC).

  • The aims of this study are to fit a logistic regression model towards the fly problem in a farm and to identify the variables that are associated with the fly problem in a poultry farm. By using SPSS software, this study used ‘FORWARD STEPWISE’ and ‘BACKWARD STEPWISE’ methods to perform the analysis. Compared to linear regression analysis, logistic regression does not require rigorous assumptions to be met. This study used Likelihood Ratio test, Omnibus test and Hosmer and Lemeshow test to validate and to test the fit of poultry farm data. Akaike Information Criterion (AIC) is calculated to observe the difference between the methods of stepwise used by SPSS software in this study. As a result, logistic regression is fit towards poultry farm data by a stepwise procedure. BACKWARD STEPWISE seems to be more suitable for conducting the stepwise method of analysis. Besides, variables that influence the problem of fly in a poultry are the wasps, distance and number of flies.

     

  • References

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  • How to Cite

    Afiqah Muhamad Jamil, S., Asrul Affendi Abdullah, M., Sie Long, K., Fazilla Mohd Jupri, N., & Mamat, M. (2018). A Stepwise Logistic Regression Analysis: An application toward Poultry Farm Data in Johor. International Journal of Engineering & Technology, 7(3.28), 68-71. https://doi.org/10.14419/ijet.v7i3.28.20968