Change-Point Models in Logistic Regression

• 발행기관: 한국자료분석학회
• 저자명: Kwang Mo Jeong Young Hee Hong
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.2 No.1, 109~119쪽, 전체 11쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2000.03.30

영문 초록

In this paper we consider a change-point logistic regression model on hazard rates. We estimate both the logistic regression parameters and the change-point using the maximum loglikelihood function. The maximum likelihood estimation of logistic regression parameters for any fixed change-point are obtained by the Newton-Raphson iterative algorithm. As a byproduct of this algorithm we can also obtain the covariance matrix of estimated parameters. We discuss a model selection procedure based on the Schwarz information criterion. We also checked model goodness-of-fit in the respect of signed deviance residuals. The suggested change-point logistic model was explained through a real data set of head-and-neck cancer survival times. The proposed change-point logistic regression model performed quite well compared to a single logistic model with no change-point.

목차

1. Introduction

2. Change-Point Logistic Regression Model

3. Model Comparison Criterion

4. A Practical Example

5. Summary and further works

References