| CONFIDENCE LOWER LIMITS FOR RESPONSE PROBABILITIES UNDER THE LOGISTIC RESPONSE MODEL |
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| 引用本文： | TIANYubin LIGuoying YANGJie. CONFIDENCE LOWER LIMITS FOR RESPONSE PROBABILITIES UNDER THE LOGISTIC RESPONSE MODEL[J]. 系统科学与复杂性, 2004, 17(2): 289-296 |
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| 作者姓名： | TIANYubin LIGuoying YANGJie |
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| 作者单位： | TIAN Yubin (Department of Applied Mathematics，Beijing Institute of Technology，Beijing 100081，China)LI Guoying(Academy of Mathematics and Systems Science，Chinese Academy of Sciences，Beijing 100080，China)YANG Jie(Department of Applied Mathematics，Beijing Institute of Technology，Beijing 100081，China) |
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| 摘 要： | The lower confidence limits for response probabilities based on binary response data under the logistic response model are considered by saddlepoint approach. The high order approximation to the conditional distribution of a statistic for an interested parameter and then the lower confidence limits of response probabilities are derived. A simulation comparing these lower confidence limits with those obtained from the asymptotic normality is conducted. The proposed approximation is applied to two real data sets. Numerical results show that the saddlepoint approximations are much more accurate than the asymptotic normality approximations, especially for the cases of small or moderate sample sizes.
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| 关 键 词： | 逻辑响应 鞍点近似 响应概率 二进制响应数据 |
CONFIDENCE LOWER LIMITS FOR RESPONSE PROBABILITIES UNDER THE LOGISTIC RESPONSE MODEL |
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| TIAN Yubin. CONFIDENCE LOWER LIMITS FOR RESPONSE PROBABILITIES UNDER THE LOGISTIC RESPONSE MODEL[J]. Journal of Systems Science and Complexity, 2004, 17(2): 289-296 |
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| Authors: | TIAN Yubin |
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| Abstract: | The lower confidence limits for response probabilities based on binary response data under the logistic response model are considered by saddlepoint approach. The high order approximation to the conditional distribution of a statistic for an interested parameter and then the lower confidence limits of response probabilities are derived. A simulation comparing these lower confidence limits with those obtained from the asymptotic normality is conducted. The proposed approximation is applied to two real data sets. Numerical results show that the saddlepoint approximations are much more accurate than the asymptotic normality approximations, especially for the cases of small or moderate sample sizes. |
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| Keywords: | Binary response data the logistical response model saddlepoint approxima-tion. |
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