×

Inferences in linear mixed models with skew-normal random effects. (English) Zbl 1314.62072

Summary: For the linear mixed model with skew-normal random effects, this paper gives the density function, moment generating function and independence conditions. The noncentral skew chi-square distribution is defined and its density function is shown. The necessary and sufficient conditions under which a quadratic form is distributed as noncentral skew chi-square distribution are obtained. Also, a version of Cochran’s theorem is given, which modifies the result of T. Wang et al. [J. Multivariate Anal. 100, No. 3, 533–545 (2009; Zbl 1154.62342)] and is used to set up exact tests for fixed effects and variance components of the proposed model. For illustration, our main results are applied to a real data problem.

MSC:

62F03 Parametric hypothesis testing
62J05 Linear regression; mixed models

Citations:

Zbl 1154.62342

Software:

sn
Full Text: DOI

References:

[1] Afriat, S. N.: Orthogonal and oblique projectors and the characteristics of pairs of vector spaces. Proc. Camb. Philos. Soc., 53, 800-816 (1957) · doi:10.1017/S0305004100032916
[2] Arellano-Valle, R. B., Bolfarine, H., Lachos, V. H.: Skew-normal linear mixed models. J. Data Science, 3, 415-438 (2005) · Zbl 1077.62043
[3] Azzalini, A.: The skew-normal distribution and related multivariate families. Scand. J. Statist., 32, 159-188 (2005) · Zbl 1091.62046 · doi:10.1111/j.1467-9469.2005.00426.x
[4] Azzalini, A., Capitanio, A.: Statistical applications of the multivariate skew normal distributions. J. Roy. Statist. Soc. Ser. B, 61, 579-602 (1999) · Zbl 0924.62050 · doi:10.1111/1467-9868.00194
[5] Azzalini, A., Dalla Valle, A.: The multivariate skew-normal distribution. Biometrika, 83, 715-726 (1996) · Zbl 0885.62062 · doi:10.1093/biomet/83.4.715
[6] Baksalary, J. K.; Puntanen, S. (ed.); Pukkila, T. (ed.), Algebraic Characterizations and Statistical Implications of the Commutativity of Orthogonal Projectors, 113-142 (1987)
[7] Baltagi, B. H.: Econometric Analysis of Panel Data, Wiley, New York, 1995 · Zbl 0836.62105
[8] Diggle, P. J., Heagerty, P., Liang, K. E., et al.: Analysis of Longitudinal Data, Oxford Science, New York, 2002
[9] Ghidey, W., Lesaffre, E., Eilers, P.: Smooth random effects distribution in a linear mixed model. Biometrics, 60, 945-953 (2004) · Zbl 1274.62238 · doi:10.1111/j.0006-341X.2004.00250.x
[10] Lachos, V. H., Bolfarine, H., Arellano-Valle, R. B., et al.: Likelihood-based inference for multivariate skew-normal regression models. Comm. Statist. Theory Methods, 36, 1769-1786 (2007) · Zbl 1124.62037 · doi:10.1080/03610920601126241
[11] Lachos, V. H., Dey, D. K., Cancho, V. G.: Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective. J. Statist. Plann. Inference, 139, 4098-4110 (2009) · Zbl 1183.62048 · doi:10.1016/j.jspi.2009.05.040
[12] Lachos, V. H., Ghosh, P., Arellano-Valle, R. B.: Likelihood based inference for skew-normal independent linear mixed models. Statist. Sinica, 20, 303-322 (2010) · Zbl 1186.62071
[13] Laird, N. M., Ware, J. H.: Random effects models for longitudinal data. Biometrics, 38, 963-974 (1982) · Zbl 0512.62107 · doi:10.2307/2529876
[14] Lin, T. I., Lee, J. C.: Estimation and prediction in linear mixed models with skew-normal random effects for longitudinal data. Statist. Med., 27, 1490-1507 (2008) · doi:10.1002/sim.3026
[15] Ma, Y.; Genton, M. G.; Davidian, M.; Genton, M. G (ed.), Linear Mixed Models with Flexible Generalized Skew-Elliptical Random Effects, 339-358 (2004), Boca Raton, FL
[16] Mangder, L. S., Zeger, S. L.: A smooth nonparametric estimate of a mixing distribution using mixtures of Gaussians. J. Amer. Statist. Assoc., 91, 1141-1151 (1996) · Zbl 0882.62033 · doi:10.1080/01621459.1996.10476984
[17] Muirhead, R. J.: Aspects of Multivariate Statistical Theory, Wiley, New York, 1982 · Zbl 0556.62028 · doi:10.1002/9780470316559
[18] Pinheiro, J. C., Liu, C. H., Wu, Y. N.: Efficient algorithms for robust estimation in linear mixed-effects models using a multivariate t-distribution. J. Comput. Graph. Statist., 10, 249-276 (2001) · doi:10.1198/10618600152628059
[19] Tao, H., Palta, M., Yandell, B. S., et al.: An estimation method for the semiparametric mixed effects model. Biometrics, 55, 102-110 (1999) · Zbl 1059.62572 · doi:10.1111/j.0006-341X.1999.00102.x
[20] Tjur, T.: Analysis of variance models in orthogonal designs. Int. Stat. Rev., 52, 33-81 (1984) · Zbl 0575.62068 · doi:10.2307/1403242
[21] Verbeke, G., Lesaffre, E.: The effect of misspecifying the random effects distribution in linear mixed models for longitudinal data. Comput. Statist. Data Anal., 23, 541-556 (1997) · Zbl 0900.62374 · doi:10.1016/S0167-9473(96)00047-3
[22] Wang, T., Li, B., Gupta, A. K.: Distribution of quadratic forms under skew normal settings. J. Multivariate Anal., 100, 533-545 (2009) · Zbl 1154.62342 · doi:10.1016/j.jmva.2008.06.003
[23] Wu, L.: Mixed Effects Models for Complex Data, Chapman & Hall/CRC, Boca Raton, 2010 · Zbl 1268.62067
[24] Wu, M. X.: Introduction for Linear Mixed Effects Models, Science Press, Beijing, 2013
[25] Ye, R. D., Wang, T., Gupta, A. K.: Distribution of matrix quadratic forms under skew-normal settings. J. Multivariate Anal., 131, 229-239 (2014) · Zbl 1298.62086 · doi:10.1016/j.jmva.2014.07.001
[26] Zhang, D., Davidian, M.: Linear mixed models with flexible distributions of random effects for longitudinal data. Biometrics, 57, 795-802 (2001) · Zbl 1209.62087 · doi:10.1111/j.0006-341X.2001.00795.x
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.