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arXiv · 1906.00723

Semiparametric Analysis of the Proportional Likelihood Ratio Model and Omnibus Estimation Procedure

Yair Goldberg·Malka Gorfine
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Abstract

We provide a semi-parametric analysis for the proportional likelihood ratio model, proposed by Luo & Tsai (2012). We study the tangent spaces for both the parameter of interest and the nuisance parameter, and obtain an explicit expression for the efficient score function. We propose a family of Z-estimators based on the score functions, including an approximated efficient estimator. Using inverse probability weighting, the proposed estimators can also be applied to different missing-data mechanisms, such as right censored data and non-random sampling. A simulation study that illustrates the finite-sample performance of the estimators is presented.

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Yair Goldberg, Malka Gorfine. 2019-06-03. Semiparametric Analysis of the Proportional Likelihood Ratio Model and Omnibus Estimation Procedure. https://arxiv.org/abs/1906.00723

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