An Algorithm to Approximate the Fixed-Response Covariates in Logistic Regression Using Smoothing Splines

Abstract

We investigate the use of smoothing splines in logistic regression to estimate the covariate values that yield a fixed response probability, eg. LC50 or LD50. We develop an algorithm for a monotonic spline fit and approximate the resulting probability estimates and the fixed-response covariates. We illustrate our algorithm on data sets from studies of genetic spatial diversity.

Keywords: smoothing splines, logistic regression

Corresponding author: E-mail : cast@kmitl.ac.th

How to Cite

Citation Format

Kittichotipanit, N. ., & Jernigan, R. W. . (2018). An Algorithm to Approximate the Fixed-Response Covariates in Logistic Regression Using Smoothing Splines. CURRENT APPLIED SCIENCE AND TECHNOLOGY, 410-419.

References

Agresti, Alan (1990), Categorical Data Analysis, John Wiley and Sons.
Agresti, Alan (1996), An Introduction to Categorical Data Analysis, John Wiley and Sons.
Anscombe, F.J. (1956), “On estimating binomial response relations”, Biometrika, Vol.43(3), pp461-464.
Brumfield, Robb T., Jernigan, Robert W., McDonald, David B. and Braum, Michael J. (2001), “Evolutionary implications of divergent clines in an avian (Manacus:Aves) hybrid zone”, Evolution, Vol. 55(10), pp. 2070-2087.
Cox, D.R. and Shell, E.J. (1989), Analysis of binary data, 2nd edition, Chapman and Hall.

Author Information

Nomchit Kittichotipanit

Department of Applied Statistics, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

Robert W. Jernigan

Department of Mathematics and Statistics, American University, Washington D.C., USA.

About this Article

Journal

Vol. 5 No. 1 (2005)

Type of Manuscript

Original Research Article

Keywords

smoothing splines, logistic regression

Published

12 November 2018

An Algorithm to Approximate the Fixed-Response Covariates in Logistic Regression Using Smoothing Splines

Abstract

How to Cite

References

Author Information

Nomchit Kittichotipanit

Robert W. Jernigan

About this Article

Journal

Type of Manuscript

Keywords

Published

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