NAU publications by CHER
Faculty & staff publications
NAU faculty and staff have the opportunity to publish their findings and knowledge as authors. CHER has many researchers that have been cited multiple times in major publications for their great work. The Center for Health Equity Research has accumulated all faculty publications into one, easy to navigate database.
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Xing, Dongyuan; Huang, Yangxin; Chen, Henian; Zhu, Yiliang; Dagne, Getachew A; Baldwin, Julie A Bayesian inference for two-part mixed-effects model using skew distributions, with application to longitudinal semicontinuous alcohol data Journal Article Statistical Methods in Medical Research, pp. 1-19, 2015. @article{Xing2015, title = {Bayesian inference for two-part mixed-effects model using skew distributions, with application to longitudinal semicontinuous alcohol data}, author = {Dongyuan Xing and Yangxin Huang and Henian Chen and Yiliang Zhu and Getachew A Dagne and Julie A Baldwin}, url = {http://journals.sagepub.com/doi/10.1177/0962280215590284}, doi = {10.1177/0962280215590284}, year = {2015}, date = {2015-07-19}, journal = {Statistical Methods in Medical Research}, pages = {1-19}, abstract = {Semicontinuous data featured with an excessive proportion of zeros and right-skewed continuous positive values arise frequently in practice. One example would be the substance abuse/dependence symptoms data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyze repeated measures of semicontinuous data from longitudinal studies. In this paper, we propose a flexible two-part mixed-effects model with skew distributions for correlated semicontinuous alcohol data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: (i) a model on the occurrence of positive values using a generalized logistic mixed-effects model (Part I); and (ii) a model on the intensity of positive values using a linear mixed-effects model where the model errors follow skew distributions including skew-t and skew-normal distributions (Part II). The proposed method is illustrated with an alcohol abuse/dependence symptoms data from a longitudinal observational study, and the analytic results are reported by comparing potential models under different random-effects structures. Simulation studies are conducted to assess the performance of the proposed models and method.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Semicontinuous data featured with an excessive proportion of zeros and right-skewed continuous positive values arise frequently in practice. One example would be the substance abuse/dependence symptoms data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyze repeated measures of semicontinuous data from longitudinal studies. In this paper, we propose a flexible two-part mixed-effects model with skew distributions for correlated semicontinuous alcohol data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: (i) a model on the occurrence of positive values using a generalized logistic mixed-effects model (Part I); and (ii) a model on the intensity of positive values using a linear mixed-effects model where the model errors follow skew distributions including skew-t and skew-normal distributions (Part II). The proposed method is illustrated with an alcohol abuse/dependence symptoms data from a longitudinal observational study, and the analytic results are reported by comparing potential models under different random-effects structures. Simulation studies are conducted to assess the performance of the proposed models and method. |
2015 |
Xing, Dongyuan; Huang, Yangxin; Chen, Henian; Zhu, Yiliang; Dagne, Getachew A; Baldwin, Julie A Bayesian inference for two-part mixed-effects model using skew distributions, with application to longitudinal semicontinuous alcohol data Journal Article Statistical Methods in Medical Research, pp. 1-19, 2015. @article{Xing2015, title = {Bayesian inference for two-part mixed-effects model using skew distributions, with application to longitudinal semicontinuous alcohol data}, author = {Dongyuan Xing and Yangxin Huang and Henian Chen and Yiliang Zhu and Getachew A Dagne and Julie A Baldwin}, url = {http://journals.sagepub.com/doi/10.1177/0962280215590284}, doi = {10.1177/0962280215590284}, year = {2015}, date = {2015-07-19}, journal = {Statistical Methods in Medical Research}, pages = {1-19}, abstract = {Semicontinuous data featured with an excessive proportion of zeros and right-skewed continuous positive values arise frequently in practice. One example would be the substance abuse/dependence symptoms data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyze repeated measures of semicontinuous data from longitudinal studies. In this paper, we propose a flexible two-part mixed-effects model with skew distributions for correlated semicontinuous alcohol data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: (i) a model on the occurrence of positive values using a generalized logistic mixed-effects model (Part I); and (ii) a model on the intensity of positive values using a linear mixed-effects model where the model errors follow skew distributions including skew-t and skew-normal distributions (Part II). The proposed method is illustrated with an alcohol abuse/dependence symptoms data from a longitudinal observational study, and the analytic results are reported by comparing potential models under different random-effects structures. Simulation studies are conducted to assess the performance of the proposed models and method.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Semicontinuous data featured with an excessive proportion of zeros and right-skewed continuous positive values arise frequently in practice. One example would be the substance abuse/dependence symptoms data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyze repeated measures of semicontinuous data from longitudinal studies. In this paper, we propose a flexible two-part mixed-effects model with skew distributions for correlated semicontinuous alcohol data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: (i) a model on the occurrence of positive values using a generalized logistic mixed-effects model (Part I); and (ii) a model on the intensity of positive values using a linear mixed-effects model where the model errors follow skew distributions including skew-t and skew-normal distributions (Part II). The proposed method is illustrated with an alcohol abuse/dependence symptoms data from a longitudinal observational study, and the analytic results are reported by comparing potential models under different random-effects structures. Simulation studies are conducted to assess the performance of the proposed models and method. |