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. 2024 Dec;66(8):e202300214.
doi: 10.1002/bimj.202300214.

A Semiparametric Two-Sample Density Ratio Model With a Change Point

Jiahui Feng  1 , Kin Yau Wong  2   3 , Chun Yin Lee  2
Affiliations

A Semiparametric Two-Sample Density Ratio Model With a Change Point

Jiahui Feng et al. Biom J. 2024 Dec.

Abstract

The logistic regression model for a binary outcome with a continuous covariate can be expressed equivalently as a two-sample density ratio model for the covariate. Utilizing this equivalence, we study a change-point logistic regression model within the corresponding density ratio modeling framework. We investigate estimation and inference methods for the density ratio model and develop maximal score-type tests to detect the presence of a change point. In contrast to existing work, the density ratio modeling framework facilitates the development of a natural Kolmogorov-Smirnov type test to assess the validity of the logistic model assumptions. A simulation study is conducted to evaluate the finite-sample performance of the proposed tests and estimation methods. We illustrate the proposed approach using a mother-to-child HIV-1 transmission data set and an oral cancer data set.

Keywords: biased sampling; empirical likelihood; goodness‐of‐fit; logistic regression model; score test.

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References

    1. Bickel, P. J., F. Götze, and W. R. van Zwet. 1997. “Resampling Fewer Than n Observations: Gains, Losses, and Remedies for Losses.” Statistica Sinica 7: 1–31.
    1. Bickel, P. J., and A. Sakov. 2008. “On the Choice of m$m$ in the m$m$ out of n$n$ Bootstrap and Confidence Bounds for Extrema.” Statistica Sinica 18, no. 3: 967–985.
    1. Bondell, H. D. 2007. “Testing Goodness‐of‐Fit in Logistic Case‐Control Studies.” Biometrika 94, no. 2: 487–495.
    1. Day, G. L., W. J. Blot, D. F. Austin, et al. 1993. “Racial Differences in Risk of Oral and Pharyngeal Cancer: Alcohol, Tobacco, and Other Determinants.” JNCI: Journal of the National Cancer Institute 85, no. 6: 465–473.
    1. Deng, Y., D. Zeng, J. Zhao, and J. Cai. 2017. “Proportional Hazards Model With a Change Point for Clustered Event Data.” Biometrics 73, no. 3: 835–845.

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