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Proportional likelihood ratio models for mean regression

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  • Alan Huang
  • Paul J. Rathouz

Abstract

The proportional likelihood ratio model introduced in Luo & Tsai (2012) is adapted to explicitly model the means of observations. This is useful for the estimation of and inference on treatment effects, particularly in designed experiments and allows the data analyst greater control over model specification and parameter interpretation. Copyright 2012, Oxford University Press.

Suggested Citation

  • Alan Huang & Paul J. Rathouz, 2012. "Proportional likelihood ratio models for mean regression," Biometrika, Biometrika Trust, vol. 99(1), pages 223-229.
  • Handle: RePEc:oup:biomet:v:99:y:2012:i:1:p:223-229
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    File URL: http://hdl.handle.net/10.1093/biomet/asr075
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    Cited by:

    1. Weibin Zhong & Guoqing Diao, 2023. "Joint semiparametric models for case‐cohort designs," Biometrics, The International Biometric Society, vol. 79(3), pages 1959-1971, September.
    2. Weibin Zhong & Guoqing Diao, 2023. "Semiparametric Density Ratio Model for Survival Data with a Cure Fraction," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 217-241, April.
    3. Hua Yun Chen & Daniel E. Rader & Mingyao Li, 2015. "Likelihood Inferences on Semiparametric Odds Ratio Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1125-1135, September.
    4. Bhaskar Bhattacharya & Mohammad Al-talib, 2017. "A minimum relative entropy based correlation model between the response and covariates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(4), pages 1095-1118, September.
    5. Qiurong Cui & Zhengjun Zhang, 2018. "Max-Linear Competing Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 62-74, January.
    6. Marchese, Scott & Diao, Guoqing, 2017. "Density ratio model for multivariate outcomes," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 249-261.

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