A Stepwise Logistic Regression Analysis: An application toward Poultry Farm Data in Johor - Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, Mohd; Sie Long, Kek; Fazilla Mohd Jupri, Nur; Mamat, Mustafa (International Journal of Engineering and Technology, 2018)
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.
Keywords: Stepwise Logistic Regression Analysis; SPSS software; Akaike Information Criterion (AIC).