A proportional likelihood ratio model

作者：Luo Xiaodong^*; Tsai Wei Yann

来源：Biometrika, 2012, 99(1): 211-222.

DOI：10.1093/biomet/asr060

• Biased sampling
• Nonlinear monotonicity
• Semiparametric generalized linear model

We propose a semiparametric proportional likelihood ratio model which is particularly suitable for modelling a nonlinear monotonic relationship between the outcome variable and a covariate. This model extends the generalized linear model by leaving the distribution unspecified, and has a strong connection with semiparametric models such as the selection bias model (Gilbert et al., 1999), the density ratio model (Qin, 1998; Fokianos & Kaimi, 2006), the single-index model (Ichimura, 1993) and the exponential tilt regression model (Rathouz & Gao, 2009). A maximum likelihood estimator is obtained for the new model and its asymptotic properties are derived. An example and simulation study illustrate the use of the model.

• 出版日期2012-3