Model regresi logistik terbaik dengan metode backward

Abstract

Model regresi logistik ciapat digunakan untulc menggambarkan hubungan antara variabel respon clan beberapa variabel bebas yang tidak tinier, dimana variabel responnya berupa variabel indikator. Untuk menaksir paramatemya, digunakan metode malcsimum likelihood, dilanjutkan dengan iterasi Newton Raphson. Sedangkan untuk mengetahui kecocokan model regresinya, digunakan uji rasio likelihood dengan statistik ujinya adalah statistik G. Alcan ditentukan model regresi logistik terbaik dengan metode backward. Logistic regression model can be used to describe the nonlinear relationship between a response variable and independent variables, and the response variable is an indicator variable. Maximum likelihood is used to estimate the parameter and followed by Newton Raphson iteration. To check the fitting of the regression model, ratio likelihood test is used with statistics G as its test. It will be defined the best logistic regression model with backward ix This document is Undip Institutional Repository Collection. The author(s) or copyright owner(s) agree that UNDIP-IR may, withoui ch.anging the content, translate the submission to any medium or format for the purpose of preservation. The author(s) or copyrig4 owner(s) also agree that UNDIP-IR may keep more than one copy of this submission for purpose of security, back-up and preservation: . ( http://eprints.undip.acid 70000000-10007.*