Publication – XYSong

Book:
Song, X. Y. and Lee, S. Y. (2012). Basic and Advanced Bayesian Structural Equation Modeling: With Applications in the Medical and Behavioral Sciences. London, Wiley.

Journal Articles:

  1. Lin, Y.Q., Windmeijer, F., Song, X.Y. and Fan, Q.L. (2024). On the instrumental variable estimation with potentially many (weak) and some invalid instruments. Journal of the Royal Statistical Society, Series B, accepted.
  2. Zhou, X.X. and Song, X.Y. (2024). Joint analysis of multivariate longitudinal, survival, and imaging data. Journal of the Royal Statistical Society, Series C, accepted.
  3. Deng, Y., Li, S.Y., Sun, L.Q. and Song, X.Y. (2024). Semiparametric probit regression model with general interval-censored failure time data. Journal of Computational and Graphical Statistics, accepted.
  4. Zou, Y.D., Song, X.Y. and Zhao, Q. (2024). Order selection for heterogeneous semiparametric hidden Markov models. Statistics in Medicine, accepted.
  5. He, Y.Y., Song, X.Y. and Kang, K. (2023). Joint mixed membership modeling of multivariate longitudinal and survival data for learning the individualized disease progression. Annals of Applied Statistics, accepted.
  6. He, H.J., Cai, J.H. and Song, X.Y. (2023). Regression analysis of partially linear transformed mean residual life models. Electronic Journal of Statistics, accepted.
  7. Sun, R.Q. and Song, X.Y. (2023). A tree-based Bayesian accelerated failure time cure model for estimating heterogeneous treatment effect. Bayesian Analysis, accepted.
  8. Huan, C., Sun, R.Q. and Song, X.Y. (2024). Conditional generative adversarial networks for individualized causal mediation analysis. Journal of Causal Inference, accepted.
  9. Guo, W.W., Song, X.Y. and Cui, H.J. (2023). Homogeneity tests for high-dimensional mean vectors and covariance matrices. Statistica Sinica, accepted.
  10. Zou, Y.D., Lin, Y.Q. and Song, X.Y. (2024). Bayesian heterogeneous hidden Markov models with an unknown number of states. Journal of Computational and Graphical Statistics, 33, 15-24.
  11. Fang, L.J., Li, S.W., Sun, L.Q. and Song, X.Y. (2024). Semiparametric probit regression model with misclassified current status data. Statistics in Medicine, 42, 4440-4457.
  12. Wang, B. and Song, X.Y. (2024). Threshold estimation in proportional mean residual life model. Statistica Sinica, 34, 111-132.
  13. Jiang, J.J., Wang, C.J., Pan, D. and Song, X.Y. (2024). Transformation models with informative partly interval-censored data. Statistics and Computing, 34, 8.
  14. Wang, C.C. and Song, X.Y. (2024). Nonparametric quantile scalar-on-image regression. Computational Statistics and Data Analysis, 191, 107873.
  15. Sun, R.Q. and Song, X.Y. (2024). Bayesian tree-based heterogeneous mediation analysis with a time-to-event outcome. Statistics and Computing, 34, 24.
  16. Zhou, X.X. and Song, X.Y. (2023). Functional concurrent hidden Markov model. Statistics and Computing, 33, 57.
  17. He, Y.F. Feng, Y. and Song, X.Y. (2023). Variable selection for high dimensional generalized linear model with block-missing data. Scandinavian Journal of Statistics, 50, 1279-1297.
  18. Zhou, X.X. and Song, X.Y. (2023). Causal mediation analysis for Cox model with multivariate longitudinal data. Structural Equation Modeling: A Multidisciplinary Journal, 30, 749-760.
  19. Zhang, J.M., Lin, Y.Q., Song, X.Y. and Ning, H.W. (2023). Generative adversarial mediation network: A novel generative learning approach to causal mediation analysis. Knowledge-Based Systems, 282, 111117.
  20. Xi, W.Z., Li, Z.F., Song, X.Y. and Ning, H.W. (2023). Online portfolio selection with predictive instantaneous risk assessment. Pattern Recognition, 144, 109872.
  21. Yu, C.R., Guo, W.W., Song, X.Y. and Cui, H.J. (2023). Feature screening with latent responses. Biometrics, 79, 878-890.
  22. Shen, H.L, Zhang, H. and Song, X.Y. (2023). Joint deep learning for covariate decomposition and treatment effect estimation. Structural Equation Modeling: A Multidisciplinary Journal, 30, 547-559.
  23. Kang K. and Song, X.Y. (2023). Joint modeling of longitudinal imaging and survival data. Journal of Computational and Graphical Statistics, 32, 402-412.
  24. Yang, Q., Wang, C.C., He, H., Zhou, X. and Song, X.Y. (2023). Additive hazards model with time-varying coefficients and imaging predictors. Statistical Methods and Medical Research, 32, 353-372.
  25. Yang, Q., He, H.J. and Song, X.Y. (2023). Generalized Structural Equation Model with Survival Outcomes and Time-varying Coefficients. Structural Equation Modeling: A Multidisciplinary Journal, 30, 40-52.
  26. Song, Z.F., Song, X.Y. and Li, Y. (2023). Bayesian Analysis of ARCH-M model with a dynamic latent variable. Econometrics and Statistics, 28, 47-62.
  27. Wang, C.C., Yang, Q., Zhou, X.X. and Song, X.Y. (2023). Bayesian quantile latent factor on image regression. Structural Equation Modeling: A Multidisciplinary Journal, 30, 70-85.
  28. Jin J., Song, X.Y. and Sun, L.Q. (2022). Dynamic semiparametric transformation models for recurrent event data with a terminal event. Statistics in Medicine, 41, 5432-5447.
  29. Wang, S.Y., Wang, C.J., Song, X.Y. and Xu, D. (2022). Joint analysis of informatively interval-censored failure time and panel count data. Statistical Methods in Medical Research, 31, 2054-2086.
  30. Lin, Y.Q. and Song, X.Y. (2022). Order selection for regression-based hidden Markov model. Journal of Multivariate Analysis, 192, 105061.
  31. Pan, D., Song, X.Y. and Pan, J.H. (2022). Joint analysis of multivariate failure time data with latent variables. Statistical Methods in Medical Research, 31, 1292-1312.
  32. Sun, L.Q., Li, S.W., Wang, L.M., Song, X.Y. and Sui, X.M. (2022). Simultaneous variable selection in regression analysis of multivariate interval-censored data. Biometrics, 78, 1402-1413.
  33. Xiao, J.X., Yu, P., Song, X.Y. and Zhang, Z.Z. (2022). Statistical inference in partial functional linear expectile regression model. Science China Mathematics, 65, 2601-2630.
  34. Sun, X.W., Song, X.Y. and Sun, L.Q. (2022). Additive hazards regression of event history studies with intermittently measured covariates. The Canadian Journal of Statistics, 50, 511-532.
  35. Zhou, X.X., Kang, K., Kwok, T. and Song, X.Y. (2022). Joint hidden Markov model for longitudinal and time-to-event data with latent variables. Multivariate Behavioral Research, 57, 441-457.
  36. Liu, H.F., Song, X.Y. and Zhang, B.X. (2022). Varying-coefficient hidden Markov models with zero-effect regions, Computational Statistics and Data Analysis, 173, 107482.
  37. Tang, Y.L., Song, X.Y. and Yi, G.Y. (2022). Bayesian analysis under accelerated failure time models with error-prone time-to-event Outcomes. Life-time Data Analysis, 28, 139-168.
  38. Yang, Q., He, H.J. and Song, X.Y. (2022). Time-varying coefficient additive hazards model with latent variables. Statistical Methods in Medical Research, 31, 928-946.
  39. Wang, C.J., Jiang, J.J. and Song, X.Y. (2022). Bayesian transformation models with partly interval-censored data. Statistics in Medicine, 41, 1263-1279.
  40. Wang, X.R., Qin, G.Y., Song, X.Y. and Tang, Y.L. (2022). Censored quantile regression based on multiply robust propensity scores. Statistical Methods in Medical Research, 31, 475-487.
  41. Yang, Q., He, H.J., Lu, B. and Song, X.Y. (2022). Mixture additive hazards cure model with latent variables: Application to corporate default data. Computational Statistics and Data Analysis, 167, 107365.
  42. Kang K., Pan D. and Song, X.Y. (2022). A joint model for multivariate longitudinal and survival data to discover the conversion to Alzheimer’s disease. Statistics in Medicine, 41, 356-373.
  43. Kang, K. and Song, X.Y. (2022). Consistent estimation of a joint model for multivariate longitudinal and survival data with latent variables. Journal of Multivariate Analysis, 187, 104827.
  44. He, H.J., Han, D.X., Song, X.Y. and Sun, L.Q. (2021). Mixture proportional hazards cure model with latent variables. Statistics in Medicine, 40, 6590-6604.
  45. Wang, X. Q., Wu, H. T., Feng, X. N. and Song, X. Y. (2021). Bayesian two-level model for repeated partially ordered responses: application to adolescent smoking behavior analysis. Sociological Methods & Research, 50, 1515-1551.
  46. Zhou, J., Chen, X., Song, X. Y. and Sun, L. Q. (2021). A joint modeling approach for analyzing marker data in the presence of a terminal event. Biometrics, 77, 150-161.
  47. Sun L. Q., Li S. W., Wang L., Song X. Y. (2021). A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup. Statistical Methods in Medical Research, 30, 1890-1903.
  48. Sun R. Q., Zhou X. X., Song X. Y. (2021). Bayesian causal mediation analysis with latent mediators and survival outcome. Structural Equation Modeling, 28, 778-790.
  49. Wang X. Q., Song X. Y., Zhu H. T. (2021). Bayesian latent factor on image regression with nonignorable missing data. Statistics in Medicine, 40, 920-932.
  50. Li T., Song X. Y., Zhang Y. Y., Zhu H. T., Zhu Z. Y. (2021). Clusterwise functional linear regression models. Computational Statistics and Data Analysis, 158, 107192.
  51. Zhang J. M., Li Z. F., Song X. Y., Ning H. W. (2021). Deep Tobit networks: A novel machine learning approach to microeconometrics. Neural Networks, 144, 279-296.
  52. Han D. X., He H. J., Sun J. Q., Song X. Y., Xu W. (2021). Inference in a mixture additive hazards cure model. Statistics and Its Interface, 14, 323-338.
  53. Pan D., Wei Y. Y., Song X. Y. (2021). Joint analysis of mixed types of Outcomes with latent variables. Statistics in Medicine, 40, 1272-1284.
  54. Zhou X. X., Song X. Y. (2021). Mediation analysis for mixture Cox proportional hazards cure models. Statistical Methods in Medical Research, 30, 1554-1572.
  55. Wang C. J., Zhao B., Luo L. L., Song X. Y. (2021). Regression analysis of current status data with latent variables. Lifetime Data Analysis, 27, 413-436.
  56. Liu, H. F., Song, X. Y., Tang, Y. L. and Zhang, B. X. (2021). Bayesian quantile non-homogeneous hidden Markov models. Statistical Methods in Medical Research, 30, 112-128.
  57. Liu, H. F. and Song, X. Y. (2021). Bayesian analysis of hidden Markov structural equation models with an unknown number of hidden states. Econometrics and Statistics, 18, 29-43.
  58. Zhou, J., Song, X. Y. and Sun, L. Q. (2020). Continuous time hidden Markov model for longitudinal data. Journal of Multivariate Analysis, 179, 104646.
  59. Feng, X. N., Li, T. F., Song, X. Y. and Zhu, H. T. (2020). Bayesian scalar on image regression with non-ignorable non-response. Journal of the American Statistical Association, 115, 1574-1597.
  60. Wang, X. Q., Feng, X. N. and Song, X. Y. (2020). Joint analysis of semicontinuous data with latent variables. Computational Statistics and Data Analysis, 151, 107005.
  61. Ouyang, M. and Song, X. Y. (2020). Bayesian local influence of generalized failure time models with latent variables and multivariate censored data. Journal of Classification, 37, 298-316.
  62. Tian, Y. Z. and Song, X. Y. (2020). Bayesian bridge-randomized penalized quantile regression. Computational Statistics and Data Analysis, 144, 106876.
  63. Zhou, X., Kang, K. and Song, X. Y. (2020). Two-part hidden Markov models for semicontinuous longitudinal data with nonignorable missing covariates. Statistics in Medicine, 39, 1801-1816.
  64. Tian, Y. Z. and Song, X. Y. (2020). Fully Bayesian L_{1/2}-penalized linear quantile regression analysis with autoregressive errors. Statistics and Its Interface, 13, 271-286.
  65. Liu, X. Q., Song, X. Y. and Zhou, Y. (2019). Likelihood ratio-type tests in weighted composite quantile regression of DTARCH models. Science China Mathematics, 62, 2571-2590.
  66. Wang, C. J., Li, Q., Song, X. Y. and Dong, X. G. (2019). Bayesian adaptive lasso for additive hazard regression with current status data. Statistics in Medicine, 38, 3703-3718.
  67. Feng, X. N., Lu, B., Song, X. Y. and Ma, S. (2019). Financial literacy and household finances: A Bayesian two-part latent variable modeling approach. Journal of Empirical Finance, 51, 119-137.
  68. Sun, L. Q., Li, S. W., Wang, L. M. and Song, X. Y. (2019). Variable selection in semiparametric non-mixture cure model with interval-censored failure time data: an application to the prostate cancer screening study. Statistics in Medicine, 38, 3026-3039.
  69. Kang K., Cai, J. H., Song, X. Y. and Zhu, H. T. (2019). Bayesian hidden Markov models for delineating the pathology of Alzheimer’s disease. Statistical Methods in Medical Research, 28, 2112-2124.
  70. Ye, M., Lu, Z. H., Li, Y. M. and Song, X. Y. (2019). Finite mixture of varying coefficient model: Estimation and component selection. Journal of Multivariate Analysis, 171, 452-474.
  71. Kang, K., Song, X. Y., Hu, X. J. and Zhu, H. T. (2019). Bayesian adaptive group lasso with semiparametric hidden Markov models. Statistics in Medicine, 38, 1634-1650.
  72. He, H. J., Pan, D., Song, X. Y. and Sun, L. Q. (2019). Additive mean residual life model with latent variables under right censoring. Statistica Sinica, 29, 47-66.
  73. Pan, D., Kang, K., Wang, C. J. and Song, X. Y. (2019). Bayesian proportional hazards model with latent variables. Statistical Methods in Medical Research, 28, 986-1002.
  74. Ouyang, M., Wang, X. Q., Wang, C. J. and Song, X. Y. (2018). Bayesian semiparametric failure time models for multivariate censored data with latent variables. Statistics in Medicine, 37, 4279-4297.
  75. Qu, L. Q., Sun, L. Q. and Song, X. Y. (2018). A Joint Modeling Approach for Longitudinal Data with Informative Observation Times and a Terminal Event. Statistics in Bioscience, 10, 609-633.
  76. Qu, L. Q., Song, X. Y. and Sun, L. Q. (2018). Identification of local sparsity and variable selection for varying coefficient additive hazards models. Computational Statistics and Data Analysis, 125, 119-135.
  77. Cai, J. H., Ouyang, M., Kang, K. and Song, X. Y. (2018). Bayesian diagnostics of hidden Markov structural equation models with missing data. Multivariate Behavioral Research, 23, 151-171.
  78. Song, X. Y., Kang, K., Ouyang, M., Jiang, X. J. and Cai, J. H. (2018). Bayesian analysis of semiparametric hidden Markov models with latent variables. Structural Equation Modeling – A Multidisciplinary Journal, 25, 1-20.
  79. Wang, G. C. and Song, X.Y. (2018). Functional sufficient dimension reduction for functional data classification. Journal of Classification, 35, 250-272.
  80. Liu, H. F. and Song, X. Y. (2018). Bayesian analysis of mixture structural equation models with an unknown number of components. Structural Equation Modeling – A Multidisciplinary Journal, 25, 41-45.
  81. Li, J. B., Lian, H., Jiang X. J. and Song, X. Y. (2018). Estimation and testing for time-varying quantile single-index models with longitudinal data. Computational Statistics and Data Analysis, 118, 66-83.
  82. Feng, X. N., Wu, H. T. and Song, X. Y. (2017). Bayesian adaptive lasso for ordinal regression with latent variables. Sociological Methods and Research, 46, 926-953.
  83. Song, X. Y., Xia, Y. M. and Zhu, H. T. (2017). Hidden Markov latent variable models with multivariate longitudinal data. Biometrics, 73, 313-323.
  84. Ouyang M., Yan, X. D., Chen, J., Tang, N. S. and Song, X. Y. (2017). Bayesian local influence of semiparametric structural equation models. Computational Statistics and Data Analysis, 111, 102-115.
  85. Feng, X. N., Wu, H. T., and Song, X. Y. (2017). Bayesian regularized multivariate generalized latent variable models. Structural Equation Modeling – A Multidisciplinary Journal, 24, 341-358.
  86. He, H. J., Pan, D., Sun, L. Q., Li, Y. M., Robison L. and Song, X. Y. (2017). Analysis of a fixed center effect additive rates model for recurrent event data. Computational Statistics and Data Analysis, 112, 186-197.
  87. He, H. J., Cai, J. H., Song, X. Y. and Sun, L. Q. (2017). Analysis of proportional mean residual life model with latent variables. Statistics in Medicine, 36, 813-826.
  88. Feng, X. N., Wang, Y. F., Lu, B. and Song, X. Y. (2017). Bayesian regularized quantile structural equation models. Journal of Multivariate Analysis, 154, 234-248.
  89. Cai, J. H., He, H. J., Song, X. Y. and Sun, L. Q. (2017). An additive-multiplicative mean residual life model for right censored data. Biometrical Journal, 59, 579-592.
  90. Zhao, W. H., Lian, H. and Song, X. Y. (2017). Composite quantile regression for correlated data. Computational Statistics and Data Analysis, 109, 15-33.
  91. Liu, X., Song, X. Y., Xie, S. Y. and Zhou, Y. (2016). Variable selection for frailty transformation models with application to diabetic complications. The Canadian Journal of Statistics, 44, 375-394.
  92. Han, M., Song X. Y., Sun, L. Q., and Liu, L. (2016). An additive-multiplicative mean model for marker data contingent on recurrent event with an informative terminal event. Statistica Sinica, 26, 1197-1218.
  93. Song, X. Y., Pan, D., Liu, P. F. and Cai, J. H. (2016). Bayesian analysis of transformation latent variable models with multivariate censored data. Statistical Methods in Medical Research, 25, 2337-2358.
  94. Jiang, X. J., Song, X. Y. and Xiong, Z. D. (2016). Efficient and robust estimation of GARCH models. Journal of Testing and Evaluation, 44, 1828-1839.
  95. Pan, D., He, H. J., Song, X. Y. and Sun, L. Q. (2015). Regression analysis of additive hazards model with latent variables. Journal of the American Statistical Association, 110, 1148-1159.
  96. Wang, Y. F., Feng, X. N. and Song, X. Y. (2015). Bayesian quantile structural equation models. Structural Equation Modeling – A Multidisciplinary Journal, 23, 246-258.
  97. Feng, X. N., Wang, G. C., Wang, Y. F. and Song, X. Y. (2015). Structure detection of semiparametric structural equation models with Bayesian adaptive group lasso. Statistics in Medicine, 34, 1527-1547.
  98. Tang, Y. L., Song, X. Y. and Zhu, Z. Y. (2015). Threshold effect test in censored quantile regression. Statistics and Probability Letters, 105, 149-156.
  99. Liu, P. F., Chen, J., Lu, Z. H. and Song, X. Y. (2015). Transformation structural equation models with highly non-normal and incomplete data. Structural Equation Modeling – A Multidisciplinary Journal, 22, 401-415.
  100. Tang, Y. L., Song, X. Y. and Zhu, Z. Y. (2015). Variable selection via composite quantitle regression with dependent errors. Statistica Neerlandica, 69, 1-20.
  101. Zhou, L., Lin, H. Z., Song, X. Y. and Li, Y. (2014). Selection of latent variables for multiple mixed-outcome models. Scandinavian Journal of Statistics, 41, 1064-1082.
  102. Han, M., Song, X. Y., Sun, L. Q., and Liu, L. (2014). Joint modeling of longitudinal data with informative observation times and dropouts. Statistica Sinica, 24, 1487-1504.
  103. Lee, S. Y. and Song, X. Y. (2014). Bayesian structural equation model. WIRES: Computational Statistics, 6, 276-287.
  104. Song, X. Y., Cai, J. H., Feng, X. N. and Jiang, X. J. (2014). Bayesian analysis of functional-coefficient autoregressive heteroscedastic model. Bayesian Analysis, 9, 371-396.
  105. Hao, M. L., Song, X. Y. and Sun, L. Q. (2014). Reweighting Estimators for Additive Hazards Model with Missing Covariates. The Canadian Journal of Statistics, 42, 285-307.
  106. Song, X. Y., Lu, Z. H. and Feng, X. N. (2014). Latent variable models with nonparametric interaction effects of latent variables. Statistics in Medicine, 33, 1723-1737.
  107. Jiang, X. J., Jiang, J, C. and Song, X. Y. (2014). Weighted composite quantile regression estimation of DTARCH models. Econometrics Journal, 17, 1-23.
  108. Guo, X. P., Song, X. Y. and Zhang, Y. (2014). First passage optimality for continuous-time Markov decision processes with varying discount factors and history-dependent polices. IEEE Transactions on Automatic Control, 59, 163-174.
  109. Chen, J., Liu, P. F. and Song, X. Y. (2013). Bayesian diagnostics of transformation structural equation models. Computational Statistics and Data Analysis, 68, 111-128.
  110. Song, X. Y., Chen, F. and Lu, Z. H. (2013). A Bayesian semiparametric dynamic two-level structural equation model for analyzing non-normal longitudinal data. Journal of Multivariate Analysis, 121, 87-108.
  111. Pan, J. H., Song, X. Y. and Ip, H. S. (2013). A Bayesian analysis of generalized latent curve mixture models. Statistics and Its Interface, 6, 27-44.
  112. Tang, Y. L, Song, X. Y., Wang, H. X. and Zhu, Z. Y. (2013). Variable selection in high-dimensional quantile varying coefficient models. Journal of Multivariate Analysis, 122, 115-132.
  113. Song, X. Y., Lu, Z. H., Cai, J. H. and Ip, H. S. (2013). A Bayesian modeling approach for generalized semiparametric structural equation models. Psychometrika, 78, 624-647.
  114. Song, X. Y., Tang, N. S. and Chow, S. M. (2012). A Bayesian approach for generalized random coefficient structural equation models for longitudinal data with adjacent time effects. Computational Statistics and Data Analysis, 56, 4190-4203.
  115. Li, Y. X., Yutaka, K., Pan, J. H. and Song, X. Y. (2012). A criterion-based model comparison statistic for structural equation models with heterogeneous data. Journal of Multivariate Analysis, 112, 92-107.
  116. Song, X. Y. and Lee, S. Y. (2012). A tutorial on Bayesian approach for analyzing structural equation models. Journal of Mathematical Psychology, 56, 135-148.
  117. Sun, L. Q., Song, X. Y., Zhou, J. and Liu, L. (2012). Joint analysis of longitudinal data with informative observation times and a dependent terminal event. Journal of the American Statistical Association, 107, 688-700.
  118. Song, X. Y., Mu, X. Y. and Sun, L. Q. (2012). Regression analysis of longitudinal data with time-dependent covariates and informative observation times. Scandinavian Journal of Statistics, 39, 248-258.
  119. Jiang, X. J., Jiang, J. C. and Song, X. Y. (2012). Oracle model selection for nonlinear models based on weighted composite quantile regression. Statistica Sinica, 22, 1479-1506.
  120. Song, X. Y. and Lu, Z. H. (2012). Semiparametric transformation models with Bayesian P-splines. Statistics and Computing, 22, 1085-1098.
  121. Sun, L. Q., Song, X. Y. and Mu, X. Y. (2012). Regression analysis for the additive hazards model with covariate errors. Communications in Statistics – Theory and Methods, 41, 1911-1932.
  122. Tang, Y. L., Wang, H., Zhu, Z. Y. and Song, X. Y. (2012). A unified variable selection approach for varying coefficient models. Statistica Sinica, 22, 601-628.
  123. Lu, Z. H. and Song, X. Y. (2012). Finite mixture varying coefficient models for analyzing longitudinal heterogeneous data. Statistics in Medicine, 31, 544-560.
  124. Sun, L. Q., Song, X. Y. and Zhang, Z. G. (2012). Mean residual life models with time-dependent coefficients under right censoring. Biometrika, 99, 185-197.
  125. Lu, B., Song, X. Y. and Li X. D. (2012). Bayesian analysis of multi-group nonlinear structural equation models with application to behavioral finance. Quantitative Finance, 12, 477-488.
  126. Guo, X. P., Huang, Y. H. and Song, X. Y. (2012). Linear programming and constrained average optimality for general continuous-time Markov decision processes in history-dependent policies. SIAM Journal on Control and Optimization, 50, 23-47.
  127. Guo, X. P. and Song, X. Y. (2011). Discounted continuous-time constrained Markov decision processes in polish spaces. Annals of Applied Probability, 21, 2016-2049.
  128. Kwok, T., Pan, J. H. Lo, R. and Song, X. Y. (2011). The influence of participation on health related quality of life in stroke patients. Disability and Rehabilitation, 33, 1990-1996.
  129. Song, X. Y.and Lu, Z. H. (2011). Response to “Comments on `Bayesian variable selection for disease classification using gene expression data’ ”. Bioinformatics, 27, 2169-2170.
  130. Guo, X. P., Huang, Y. H. and Song, X. Y. (2011). Performance analysis for controlled semi-Markov systems with application to maintenance. Journal of Optimization Theory and Applications, 150, 295-415.
  131. Cai, J. H., Song, X. Y., Lam, K.H. and Ip, H. S. (2011). A mixture of generalized latent variable models for mixed mode and heterogeneous data. Computational Statistics and Data Analysis, 55, 2889-2907.
  132. Sun, L. Q., Song, X. Y. and Zhou, J. (2011). Regression analysis of longitudinal data with time-dependent covariates in the presence of informative observation and censoring times. Journal of Statistical Planning and Inference, 141, 2902-2919.
  133. Song, X. Y., Lu, Z. H., Hser, Y. I. and Lee, S. Y. (2011). A Bayesian approach for analyzing longitudinal structural equation models. Structural Equation Modeling – A multidisciplinary Journal, 18, 183-194.
  134. Chow, S. M., Tang, N. S., Yuan, Y., Song, X. Y. and Zhu, H. T. (2011). Bayesian estimation of semiparametric nonlinear dynamic factor analysis models using the Dirichlet process prior. British Journal of Mathematical and Statistical Psychology, 64, 69-106.
  135. Song, X. Y., Xia, Y. M., Pan, J. H. and Lee, S. Y. (2011). Model comparison of Bayesian semiparametric and parametric structural equation models. Structural Equation Modeling – A Multidisciplinary Journal, 18, 55-72.
  136. Chen, F., Zhu, H. T., Song, X. Y. and Lee, S. Y. (2010). Perturbation selection and local influence analysis for generalized linear mixed models. Journal of Computational and Graphical Statistics, 19, 826-842.
  137. Cai, J. H. and Song, X. Y. (2010). Bayesian analysis of mixtures in structural equation models with nonignorable missing data. British Journal of Mathematical and Statistical Psychology, 63, 491-508.
  138. Song, X. Y., Sun, L. Q., Mu, X. Y. and Dinse, G. E. (2010). Additive hazards regression with censoring indicators missing at random. The Canadian Journal of Statistics, 38, 333-351.
  139. Song, X. Y. and Lu, Z. H. (2010). Semiparametric latent variable models with Bayesian P-splines. Journal of Computational and Graphical Statistics, 19, 590-608.
  140. Cai, J. H., Song, X. Y. and Hser, Y. I. (2010). A Bayesian analysis of mixture structural equation models with nonignorable missing responses and covariates. Statistics in Medicine, 29, 1861-1874.
  141. Song, X. Y., Pan, J. H., Kwok, T., Vandenput, L., Ohlsson, C. and Leung, P. C. (2010). A semiparametric Bayesian approach for structural equation models. Biometrical Journal, 52, 314-332.
  142. Lee, S. Y., Song, X. Y. and Cai, J. H. (2010). A Bayesian approach for nonlinear structural equation models with dichotomous variables using logit and probit links. Structural Equation Modeling – A Multidisciplinary Journal, 17, 280-302.
  143. Yang, A. J. and Song, X. Y. (2010). Bayesian variable selection for disease classification using gene expression data. Bioinformatics, 26, 215-222.
  144. Pan, J. H., Song, X. Y. and Kwok, T. (2009). Application of latent curve models in medical research – A review. European Neurological Review, 4, 52-56.
  145. Guo, X. P. and Song, X. Y. (2009). Mean-variance criteria for finite continuous-time Markov decision processes. IEEE Transactions on Automatic Control, 54, 2151-2157.
  146. Xia, Y. M., Song, X. Y. and Lee, S. Y. (2009). Robustifying model fitting for the nonlinear structural equation model under normal theory. British Journal of Mathematical and Statistical Psychology, 62, 529-568.
  147. Guo, X. P., Song, X. Y. and Zhang, J. Y. (2009). Bias optimality for multichain continuous-time Markov decision process. Operation Research Letters. 37, 317-321.
  148. Song, X. Y., Lee, S. Y., Ma, R. C. W, So, W. Y., Cai, J. H., Ying, W., Tam, C., Lam, V., Ng, M. C. Y. and Chan, J. C. N. (2009). Phenotype-genotype interactions on renal function in type 2 diabetes – An analysis using structural equation modeling. Diabetologia, 52, 1543-1553.
  149. Song, X. Y., Xia, Y. M. and Lee, S. Y. (2009). Bayesian semiparametric analysis of structural equation models with mixed continuous and unordered categorical variables. Statistics in Medicine, 28, 2253-2276.
  150. Song, X. Y., Lee, S. Y. and Hser, Y. I. (2009). Bayesian analysis of multivariate latent curve models with nonlinear longitudinal latent effects. Structural Equation Modeling – A Multidisciplinary Journal, 16, 245-266.
  151. Lee, S. Y., Song, X. Y., Cai, J. H., So, W. Y., Ma, C. W. and Chan, C. N. J. (2009). Non-linear structural equation models with correlated continuous and discrete data. British Journal of Mathematical and Statistical Psychology, 62, 327-347.
  152. Pan, J. H., Song, X. Y., Lee, S. Y. and Kwok, T. (2008). Longitudinal analysis of quality of life for stroke survivors using latent curve models. Stroke, 39, 2795-2802.
  153. Song, X. Y., Lee, S. Y. and Hser, Y. I. (2008). A two-level structural equation model approach for analyzing multivariate longitudinal responses. Statistics in Medicine, 27, 3017-3041.
  154. Cai, J. H., Song, X. Y. and Lee, S. Y. (2008). Bayesian analysis of nonlinear structural equation models with mixed continuous, ordered and unordered categorical, and nonignorable missing data. Statistics and Its Interface, 1, 99-114.
  155. Lee, S. Y. and Song, X. Y. (2008). On Bayesian estimation and model comparison of an integrated structural equation model. Computational Statistics and Data Analysis. 52, 4814-4827.
  156. Lee, S. Y., Lu, B. and Song, X. Y. (2008). Semiparametric Bayesian analysis of structural equation models with fixed covariates. Statistics in Medicine, 27, 2341-2360.
  157. Song, X. Y. and Lee, S. Y. (2008). A Bayesian approach for analyzing hierarchical data with missing outcomes through structural equation models. Structural Equation Modeling – A Multidisciplinary Journal, 15, 272-300.
  158. Lee, S. Y., Song, X. Y. and Lu, B. (2007). Discriminant analysis using mixed continuous, dichotomous, and ordered categorical variables. Multivariate Behavioral Research, 42, 631-645.
  159. Lee, S. Y., Song, X. Y. and Tang, N. S. (2007). Bayesian methods for analyzing structural equation models with covariates, interaction, and quadratic latent variables. Structural Equation Modeling – A Multidisciplinary Journal, 14, 404-434.
  160. Lee, S. Y., Poon, W. Y. and Song, X. Y. (2007). Bayesian analysis of the factor model with finance applications. Quantitative Finance, 7, 343-356.
  161. Song, X. Y., Lee, S. Y., Ng, M. C. Y., So, W. Y. and Chan, J. C. N. (2007). Bayesian analysis of structural equation models with multinomial variable and an application to type 2 diabetic nephropathy. Statistics in Medicine, 26, 2348-2369.
  162. Song, X. Y. and Lee, S. Y. (2007). Bayesian analysis of latent variable models with non-ignorable missing outcomes from exponential family. Statistics in Medicine, 26, 681-693.
  163. Lee, S. Y. and Song, X. Y. (2007). A unified maximum likelihood approach for analyzing structural equation models with missing nonstandard data. Sociological Methods & Research, 35, 352-381.
  164. Song, X. Y. and Lee, S. Y. (2006). Bayesian analysis of structural equation models with nonlinear covariates and latent variables. Multivariate Behavioral Research, 41, 337-365.
  165. Lu, B. and Song, X. Y. (2006). Local influence analysis of multivariate probit latent variable models. Journal of Multivariate Analysis, 97, 1783-1798.
  166. Song, X. Y. and Lee, S. Y. (2006). A maximum likelihood approach for multisample nonlinear structural equation models with missing continuous and dichotomous data. Structural Equation Modeling – A Multidisciplinary Journal, 13, 325-351.
  167. Song, X. Y. and Lee, S. Y. (2006). Model comparison of generalized linear mixed models. Statistics in Medicine, 25, 1685-1698.
  168. Lee, S. Y., Lu, B. and Song, X. Y. (2006). Assessing local influence for nonlinear structural equation models with ignorable missing data. Computational Statistics and Data Analysis, 50, 1356-1377.
  169. Song, X. Y. and Lee, S. Y. (2005). Maximum likelihood analysis of nonlinear structural equation models with dichotomous variables. Multivariate Behavioral Research, 40, 151-177.
  170. Song, X. Y. and Lee, S. Y. (2005). A multivariate probit latent variable model for analyzing dichotomous responses. Statistica Sinica, 15, 645-664.
  171. Lee, S. Y., Song, X. Y., Skevington, S. and Hao, Y. T. (2005). Application of structural equation models to quality of life. Structural Equation Modeling – A Multidisciplinary Journal, 12, 435-453.
  172. Lee, S. Y. and Song, X. Y. (2005). Maximum likelihood analysis of a two-level nonlinear structural equation model with fixed covariates. Journal of Educational and Behavioral Statistics, 30, 1-26.
  173. Lee, S. Y. and Song, X. Y. (2004). Evaluation of the Bayesian and maximum likelihood approaches in analyzing structural equation models with small sample sizes. Multivariate Behavioral Research, 39, 653-686.
  174. Lee, S. Y. and Song, X. Y. (2004). Maximum likelihood analysis of a general latent variable model with hierarchically mixed data. Biometrics, 60, 624-636.
  175. Lee, S. Y., Song, X. Y. and Poon W. Y. (2004). Comparison of approaches in estimating interaction and quadratic effects of latent variables. Multivariate Behavioral Research, 39, 37-67.
  176. Song, X, Y. and Lee, S. Y. (2004). Local influence analysis for mixture of structural equation models, Journal of Classification, 21, 111-137.
  177. Song, X. Y. and Lee, S. Y. (2004). Bayesian analysis of two-level nonlinear structural equation models with continuous and polytomous data. British Journal of Mathematical and Statistical Psychology, 57, 29-52.
  178. Lee, S. Y. and Song, X. Y. (2004). Bayesian model comparison of nonlinear latent variable models with missing continuous and ordinal categorical data. British Journal of Mathematical and Statistical Psychology, 57, 131-150.
  179. Song, X. Y. and Lee, S. Y. (2004). Local influence of two-level latent variable models with continuous and polytomous data. Statistica Sinica, 14, 317-332.
  180. Lee, S. Y. and Song, X. Y. (2003). Maximum likelihood estimation and model comparison for mixtures of structural equation models with ignorable missing data. Journal of Classification, 20, 221-255.
  181. Lee, S. Y. and Song, X. Y. (2003). Maximum likelihood estimation and model comparison of nonlinear structural equation models with continuous and polytomous variables. Computational Statistics and Data Analysis, 44, 125-142.
  182. Lee, S. Y., Song, X. Y. and Lee, J. C. K. (2003). Maximum likelihood estimation of nonlinear structural equation models with ignorable missing data. Journal of Educational and Behavioral Statistics, 28, 111-134.
  183. Lee, S. Y. and Song, X. Y. (2003). Bayesian analysis of structural equation models with dichotomous variables. Statistics in Medicine, 22, 3073-3088.
  184. Lee, S. Y. and Song, X. Y. (2003). Bayesian model selection for mixtures of structural equation models with an unknown number of components. British Journal of Mathematical and Statistical Psychology, 56, 145-165.
  185. Lee, S. Y. and Song, X. Y. (2003). Model comparison of nonlinear structural equation models with fixed covariates. Psychometrika, 68, 27-47.
  186. Song, X. Y. and Lee, S. Y. (2003). Full maximum likelihood estimation of polychoric and polyserial correlations with missing data. Multivariate Behavioral Research, 38, 57-79.
  187. Song, X. Y. and Lee, S. Y. (2002). A Bayesian approach for multigroup nonlinear factor analysis. Structural Equation Modeling – A Multidisciplinary Journal, 9, 523-553.
  188. Lee, S. Y., Zhang, W. Y. and Song, X. Y. (2002). Estimation of covariance function with functional data. British Journal of Mathematical and Statistical Psychology, 55, 247-261.
  189. Song, X. Y. and Lee, S. Y. (2002). Bayesian model selection method with applications. Computational Statistics and Data Analysis, 40, 539-557.
  190. Song, X. Y. and Lee, S. Y. (2002). Bayesian estimation and model selection of multivariate linear model with polytomous variables. Multivariate Behavioral Research, 37, 453-477.
  191. Zhang, W. Y., Lee, S. Y. and Song, X. Y. (2002). Local polynomial fitting in semivary coefficient model. Journal of Multivariate Analysis, 82, 166-188.
  192. Lee, S. Y. and Song, X. Y. (2002). Bayesian selection on the number of factors in a factor analysis model. Behaviormetrika, 29, 23-40.
  193. Song, X. Y. and Lee, S. Y. (2002). Analysis of structural equation model with ignorable missing continuous and polytomous data. Psychometrika, 67, 261-288.
  194. Lee, S. Y. and Song, X. Y. (2001). Hypothesis testing and model comparison in two-level structural equation models. Multivariate Behavioral Research, 36, 639-655.
  195. Song, X. Y. and Lee, S. Y. (2001). Bayesian estimation and test for factor analysis model with continuous and polytomous data in several populations. British Journal of Mathematical and Statistical Psychology, 54, 237-263.
  196. Song, X. Y., Lee, S. Y. and Zhu, H. T. (2001). Model selection in structural equation models with continuous and polytomous data. Structural Equation Modeling – A Multidisciplinary Journal, 8, 378-396.

Book Chapters:

  1. Li, X. D., Feng, X. N., Lu, B. and Song, X. Y. (2015). The determinants of capital structure choice for Chinese listed companies based on structural equation modeling approach. In Structural Equation Modeling (SEM): Concepts, Applications and Misconceptions, Nova Science Publishers, to appear.
  2. Yang, A. J., Song, X. Y. and Li, Y. X. (2012). Multi-class classification via Bayesian variable selection with gene expression data. In F. Emmert-Streib and M. Dehmer (Eds) Statistical Diagnostics for Cancer: Analyzing High Dimensional Data. Wiley.
  3. Lee, S. Y. and Song, X. Y. (2010). Structural equation models. In E. Baker, P. Peterson and B. McGaw (Eds) International Encyclopedia of Education, 3rd Ed., Elsevier.
  4. Lee, S. Y. and Song, X. Y. (2008). Bayesian model comparison of structural equation models. In D. Dunson (Ed) Random Effect and Latent Variable Model Selection. p121-150. Springer.
  5. Song, X. Y. (2007). Analysis of multisample structural equation models with applications to quality of life. In S. Y. Lee (Ed) Handbook of Latent Variable and Related Models, p279-302, Elsevier.
  6. Lu, B., Song, X. Y., Lee, S. Y. and Lai, M. M. (2007). Local inference analysis for latent variable models with non-ignorable missing responses. In S. Y. Lee (Ed) Handbook of Latent Variable and Related Models, p 109-134, Elsevier.
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