Psychophysical Threshold Estimates in Logistic Regression Using the Bootstrap Resampling
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概要
- 論文の詳細を見る
We propose the non-parametric bootstrap resampling algorithm for the problem of psychophysical threshold estimates. We use the logistic regression with guessing rate and the log-likelihood ratio test statistics of two samples for testing the hypothesis by using the bootstrap resampling. We apply our algorithm to the visual acuity test, and show that the bootstrap resampling is useful for the problem of the two-sample test when the numbers of observations are not identical between the two samples. We also propose the bootstrap algorithm for one-sample testing to certify the values of parameters and threshold obtained by logistic regression.
著者
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Tabuchi Akio
Department Of Ophthalmology Kawasaki Medical School
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Kani Kazutaka
Department Of Anatomy Ophthalmology
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Hara Heihachiro
Department Of Health Informatics Faculty Of Health And Welfare Services Administration Kawasaki Univ
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Kani Kazutaka
Department Of Orthoptics And Visual Science School Of Science Kyushu University Of Health And Welfar
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Mita Norihiro
Department of Ophthalmology, Kanazawa Medical University
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Jianli Jiao
Department of Science, ShangHai Healthy Vocational and Technical College
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Jianli Jiao
Department Of Science Shanghai Healthy Vocational And Technical College
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Mita Norihiro
Department Of Ophthalmology Kanazawa Medical University
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Tabuchi Akio
Department Of Sensory Science Faculty Of Health Science And Technology Kawasaki University Of Medica
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Hara Heihachiro
Department Of Health Informatics Faculty Of Health And Welfare Services Administration Kawasaki Univ
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