- Improved Exact Inference in Logistic Regression Model
- Improved Exact Inference in Logistic Regression Model
- ㆍ 저자명
- Kim. Donguk,Kim. Sooyeon
- ㆍ 간행물명
- 한국통계학회 논문집
- ㆍ 권/호정보
- 2003년|10권 2호|pp.277-289 (13 pages)
- ㆍ 발행정보
- 한국통계학회
- ㆍ 파일정보
- 정기간행물|ENG| PDF텍스트
- ㆍ 주제분야
- 기타
We propose modified exact inferential methods in logistic regression model. Exact conditional distribution in logistic regression model is often highly discrete, and ordinary exact inference in logistic regression is conservative, because of the discreteness of the distribution. For the exact inference in logistic regression model we utilize the modified P-value. The modified P-value can not exceed the ordinary P-value, so the test of size $alpha$ based on the modified P-value is less conservative. The modified exact confidence interval maintains at least a fixed confidence level but tends to be much narrower. The approach inverts results of a test with a modified P-value utilizing the test statistic and table probabilities in logistic regression model.