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Consequences of misspecifying assumptions in nonlinear mixed effects models

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  • Hartford, Alan
  • Davidian, Marie

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  • Hartford, Alan & Davidian, Marie, 2000. "Consequences of misspecifying assumptions in nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 34(2), pages 139-164, August.
    • Handle: RePEc:eee:csdana:v:34:y:2000:i:2:p:139-164
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    References listed on IDEAS

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    1. Huageng Tao & Mari Palta & Brian S. Yandell & Michael A. Newton, 1999. "An Estimation Method for the Semiparametric Mixed Effects Model," Biometrics, The International Biometric Society, vol. 55(1), pages 102-110, March.
    2. Verbeke, Geert & Lesaffre, Emmanuel, 1997. "The effect of misspecifying the random-effects distribution in linear mixed models for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 23(4), pages 541-556, February.
    3. Wolfinger, Russell D. & Xihong Lin, 1997. "Two Taylor-series approximation methods for nonlinear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 465-490, September.
    4. Bengt Muthén & Kerby Shedden, 1999. "Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm," Biometrics, The International Biometric Society, vol. 55(2), pages 463-469, June.
    5. Hulin Wu & A. Adam Ding, 1999. "Population HIV-1 Dynamics In Vivo: Applicable Models and Inferential Tools for Virological Data from AIDS Clinical Trials," Biometrics, The International Biometric Society, vol. 55(2), pages 410-418, June.
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    Cited by:

    1. Zambom, Adriano Zanin & Akritas, Michael G., 2017. "NonpModelCheck: An R Package for Nonparametric Lack-of-Fit Testing and Variable Selection," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i10).
    2. Huang, Xianzheng, 2011. "Detecting random-effects model misspecification via coarsened data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 703-714, January.
    3. Vock, David & Davidian, Marie & Tsiatis, Anastasios, 2014. "SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(c02).
    4. Ruth M. Pfeiffer & Louise Ryan & Augusto Litonjua & David Pee, 2005. "A Case-Cohort Design for Assessing Covariate Effects in Longitudinal Studies," Biometrics, The International Biometric Society, vol. 61(4), pages 982-991, December.
    5. Bart Spiessens & Emmanuel Lesaffre & Geert Verbeke & KyungMann Kim, 2002. "Group Sequential Methods for an Ordinal Logistic Random-Effects Model Under Misspecification," Biometrics, The International Biometric Society, vol. 58(3), pages 569-575, September.

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