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Variances Are Not Always Nuisance Parameters

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  • Raymond J. Carroll

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  • Raymond J. Carroll, 2003. "Variances Are Not Always Nuisance Parameters," Biometrics, The International Biometric Society, vol. 59(2), pages 211-220, June.
    • Handle: RePEc:bla:biomet:v:59:y:2003:i:2:p:211-220
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    File URL: http://hdl.handle.net/10.1111/1541-0420.t01-1-00027
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    References listed on IDEAS

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    1. Bani Mallick & F. Owen Hoffman & Raymond J. Carroll, 2002. "Semiparametric Regression Modeling with Mixtures of Berkson and Classical Error, with Application to Fallout from the Nevada Test Site," Biometrics, The International Biometric Society, vol. 58(1), pages 13-20, March.
    2. Patrick J. Heagerty, 1999. "Marginally Specified Logistic-Normal Models for Longitudinal Binary Data," Biometrics, The International Biometric Society, vol. 55(3), pages 688-698, September.
    3. Daniel W. Schafer & Jay H. Lubin & Elaine Ron & Marilyn Stovall & Raymond J. Carroll, 2001. "Thyroid Cancer Following Scalp Irradiation: A Reanalysis Accounting for Uncertainty in Dosimetry," Biometrics, The International Biometric Society, vol. 57(3), pages 689-697, September.
    4. Danh V. Nguyen & A. Bulak Arpat & Naisyin Wang & Raymond J. Carroll, 2002. "DNA Microarray Experiments: Biological and Technological Aspects," Biometrics, The International Biometric Society, vol. 58(4), pages 701-717, December.
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    Cited by:

    1. Jay Verkuilen & Michael Smithson, 2012. "Mixed and Mixture Regression Models for Continuous Bounded Responses Using the Beta Distribution," Journal of Educational and Behavioral Statistics, , vol. 37(1), pages 82-113, February.
    2. Yixin Fang & Heng Lian & Hua Liang, 2018. "A generalized partially linear framework for variance functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1147-1175, October.
    3. Bailey, Natalia & Pesaran, M. Hashem & Smith, L. Vanessa, 2019. "A multiple testing approach to the regularisation of large sample correlation matrices," Journal of Econometrics, Elsevier, vol. 208(2), pages 507-534.
    4. Zengri Wang & Thomas A. Louis, 2004. "Marginalized Binary Mixed-Effects Models with Covariate-Dependent Random Effects and Likelihood Inference," Biometrics, The International Biometric Society, vol. 60(4), pages 884-891, December.
    5. Pourahmadi, Mohsen & Daniels, Michael J. & Park, Trevor, 2007. "Simultaneous modelling of the Cholesky decomposition of several covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 98(3), pages 568-587, March.
    6. Feng, Sanying & Lian, Heng & Xue, Liugen, 2016. "A new nested Cholesky decomposition and estimation for the covariance matrix of bivariate longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 102(C), pages 98-109.
    7. Guo You Qin & Zhong Yi Zhu, 2009. "Robustified Maximum Likelihood Estimation in Generalized Partial Linear Mixed Model for Longitudinal Data," Biometrics, The International Biometric Society, vol. 65(1), pages 52-59, March.
    8. Yiyun Shou & Michael Smithson, 2015. "Evaluating Predictors of Dispersion: A Comparison of Dominance Analysis and Bayesian Model Averaging," Psychometrika, Springer;The Psychometric Society, vol. 80(1), pages 236-256, March.
    9. Florian Böing-Messing & Joris Mulder, 2018. "Automatic Bayes Factors for Testing Equality- and Inequality-Constrained Hypotheses on Variances," Psychometrika, Springer;The Psychometric Society, vol. 83(3), pages 586-617, September.
    10. Qinqin Hu & Lu Lin, 2018. "Conditional feature screening for mean and variance functions in models with multiple-index structure," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(4), pages 357-393, May.
    11. Raymond J. Carroll & Douglas Midthune & Laurence S. Freedman & Victor Kipnis, 2006. "Seemingly Unrelated Measurement Error Models, with Application to Nutritional Epidemiology," Biometrics, The International Biometric Society, vol. 62(1), pages 75-84, March.
    12. You-Gan Wang & Yuning Zhao, 2007. "A Modified Pseudolikelihood Approach for Analysis of Longitudinal Data," Biometrics, The International Biometric Society, vol. 63(3), pages 681-689, September.
    13. Meihua Wu & Ana Diez†Roux & Trivellore E. Raghunathan & Brisa N. Sánchez, 2018. "FPCA†based method to select optimal sampling schedules that capture between†subject variability in longitudinal studies," Biometrics, The International Biometric Society, vol. 74(1), pages 229-238, March.

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