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Latent Subgroup Analysis of a Randomized Clinical Trial through a Semiparametric Accelerated Failure Time Mixture Model

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  • L. Altstein
  • G. Li

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  • L. Altstein & G. Li, 2013. "Latent Subgroup Analysis of a Randomized Clinical Trial through a Semiparametric Accelerated Failure Time Mixture Model," Biometrics, The International Biometric Society, vol. 69(1), pages 52-61, March.
    • Handle: RePEc:bla:biomet:v:69:y:2013:i:1:p:52-61
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2012.01818.x
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    References listed on IDEAS

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    1. Yahong Peng & Roderick J. A. Little & Trivellore E. Raghunathan, 2004. "An Extended General Location Model for Causal Inferences from Data Subject to Noncompliance and Missing Values," Biometrics, The International Biometric Society, vol. 60(3), pages 598-607, September.
    2. T. Loeys & E. Goetghebeur, 2003. "A Causal Proportional Hazards Estimator for the Effect of Treatment Actually Received in a Randomized Trial with All-or-Nothing Compliance," Biometrics, The International Biometric Society, vol. 59(1), pages 100-105, March.
    3. Zeng, Donglin & Lin, D.Y., 2007. "Efficient Estimation for the Accelerated Failure Time Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1387-1396, December.
    4. Guido W. Imbens & Donald B. Rubin, 1997. "Estimating Outcome Distributions for Compliers in Instrumental Variables Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 555-574.
    5. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    6. Robert M. Elashoff & Gang Li & Ying Zhou, 2012. "Nonparametric inference for assessing treatment efficacy in randomized clinical trials with a time-to-event outcome and all-or-none compliance," Biometrika, Biometrika Trust, vol. 99(2), pages 393-404.
    7. Jack Cuzick & Peter Sasieni & Jonathan Myles & Jonathan Tyrer, 2007. "Estimating the effect of treatment in a proportional hazards model in the presence of non‐compliance and contamination," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(4), pages 565-588, September.
    8. Zhezhen Jin & D. Y. Lin & Zhiliang Ying, 2006. "On least-squares regression with censored data," Biometrika, Biometrika Trust, vol. 93(1), pages 147-161, March.
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    Cited by:

    1. Irene Mariñas-Collado & M. Jesús Rivas-López & Juan M. Rodríguez-Díaz & M. Teresa Santos-Martín, 2021. "A New Compromise Design Plan for Accelerated Failure Time Models with Temperature as an Acceleration Factor," Mathematics, MDPI, vol. 9(8), pages 1-16, April.
    2. Shengli An & Peter Zhang & Hong-Bin Fang, 2023. "Subgroup Identification in Survival Outcome Data Based on Concordance Probability Measurement," Mathematics, MDPI, vol. 11(13), pages 1-10, June.
    3. Xifen Huang & Chaosong Xiong & Jinfeng Xu & Jianhua Shi & Jinhong Huang, 2022. "Mixture Modeling of Time-to-Event Data in the Proportional Odds Model," Mathematics, MDPI, vol. 10(18), pages 1-11, September.
    4. Sudipta Saha & Zhihui Liu & Olli Saarela, 2021. "Instrumental variable estimation of early treatment effect in randomized screening trials," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(4), pages 537-560, October.
    5. Zhang, Yuyang & Schnell, Patrick & Song, Chi & Huang, Bin & Lu, Bo, 2021. "Subgroup causal effect identification and estimation via matching tree," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
    6. Xifen Huang & Jinfeng Xu, 2022. "Subgroup Identification and Regression Analysis of Clustered and Heterogeneous Interval-Censored Data," Mathematics, MDPI, vol. 10(6), pages 1-11, March.

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