Faculty Profile

Peter X.K. Song, PhD

Peter X.K. Song, PhD

  • Professor of Biostatistics
  • M4140 SPH II
  • 1415 Washington Heights
  • Ann Arbor, Michigan 48109-2029

Peter Song is a Professor of Biostatistics at the Department of Biostatistics, School of Public Health, University of Michigan. He received his PhD in Statistics from the University of British Columbia in 1996. Prior to the appointment at the University of Michigan, he was a faculty member at the Department of Statistics and Actuarial Science, University of Waterloo (2004-2007) and a faculty member at the Department of Mathematics and Statistics, York University, Toronto (1996-2004). Peter Song's research interests include bioinformatics, longitudinal data analysis, missing data problems in clinical trials, statistical genetics, and time series analysis. He is interested in methodological developments related to modelling, statistical inference and applications in biomedical sciences. In particular, Dr. Song's research projects are strongly motivated from real world data analysis. In 2007 he published a monograph "Correlated Data Analysis: Modeling, Analytics and Applications" by Springer.

  • PhD, Statistics, University of British Columbia, 1996
  • B.S., Statistics, Jilin University, 1985

  • My research interests lie in two major fields: In the field of statistical methodology, my interests include composite likelihood method, copula, data integration, generalized linear models, longitudinal data analysis, missing data, statistical computing, spatial/spatio-temporal data analysis, and time series analysis. In the field of empirical study, my interests include asthma, bioinformatics, biomarker, chronic disease, epigenetics, environmental health sciences, nephrology, obesity, and statistical genetics.

  • Shin, YE, Sang, H, Liu, D, Ferguson, TA and Song, PXK (2019+). Autologistic Network Model on Binary Data for Disease Progression Study. Biometrics (to appear).
  • Lou, L, She, X, Cao, J, Zhang, Y, Li, Y and Song, PXK (2019+). Detection and prediction of ovulation from body temperature measured by an in-ear wearable thermometer. IEEE Transactions on Biomedical Engineering (to appear).
  • Baek, J., Zhu, B. and Song, PXK. (2019). Bayesian analysis of infant's growth dynamics with in utero exposure to environmental toxicants. Annals of Applied Statistics 13, 297-320.
  • Lu Tang, Ling Zhou, Song, PXK (2019). Fusion learning algorithm to combine partially heterogeneous Cox models. Computational Statistics 34(1): 395-414.
  • Zhang, S., Q. M. Zhou, D. Zhu and Song, PXK. (2019). Goodness-of-fit test in multivariate diffusion models. Journal of Business & Economic Statistics 37, 275-287.
  • Zhong, P., Lan, W., Song, PXK. and Tsai, C. (2017). Tests for covariance structures with high-dimensional repeated measurements. Annals of Statistics 45, 1185-1213.
  • Tang, L, and Song, PXK. (2016). Fused lasso in regression coefficients clustering – Learning parameter heterogeneity in data integration. Journal of Machine Learning Research 17, 1-23.
  • Zhou, Y. and Song, PXK. (2016). Regression analysis of networked data. Biometrika 103, 287-301.
  • Puttabyatappa, M, Banker, M, Zeng, L, Goodrich, JM, Domino, SE, Dolinoy, DC, Meeker, JD, Pennathur, S, Song, PXK, Padmanabhan, V. (2019+). Maternal exposures to environmental disruptors and sexually-dimorphic changes in maternal and neonatal oxidative stress. The Journal of Clinical Endocrinology & Metabolism (to appear).
  • Fang, Y, Scott, L, Song, PXK, Burmeister, M and Sen, S (2019+). Genomic prediction of depression risk and resilience under stress. Nature Human Behaviour (to appear).
  • Perng, W, Tamayo-Ortiz, M, Tang, L, Sanchez, BN, Alejandra Cantoral, A, John D. Meeker, JD, Dolinoy, DC, Roberts, EFS, Angeles Martinez Mier, AM, Hector Lamadrid-Figueroa, H, Song, PXK, Adrienne Ettinger, A, Wright, R, Arora, M, Schnaas, L, Watkins, DJ, Goodrich, JM,. Garcia, RC, Solano-Gonzalez, M, Bautista-Arredondo, LF, Mercado-Garcia, A, Hu, H, Hernandez-Avila, M, Tellez-Rojo, MM, and Peterson, KE (2019+). The Early Life Exposure in Mexico to Environmental Toxicants (ELEMENT) Project. British Medical Journal Open (to appear).
  • Jansen, E.C., Dunietz, G.L., Dababneh, A., Peterson, K.E., Chervin, R.D., Baek, J., O’Brien, L., Song, PXK., Cantoral, A., Hu, H. and Tellez-Rojo, M.M. (2019+). Cumulative childhood lead levels in relation to sleep during adolescence. Journal of Clinical Sleep Medicine (to appear).
  • Neier, K., Cheatham, D., Bedrosian, L.D., Gregg, B.E., Song, PXK, Dolinoy, D.C. (2019+) Longitudinal Metabolic Impacts of Perinatal Exposure to Phthalates and Phthalate Mixtures in Mice. Endocrinology (to appear).
  • Perng, W., Tang, L., Song, PXK, Goran, M., Tellez-Rojo, M.M., Cantoral, A. and Peterson, K. (2019+). Urate and nonanoate mark the relationship between sugar-sweetened beverage intake and blood pressure in adolescent girls: A metabolomics analysis in the ELEMENT Cohort. Metabolites (to appear).
  • Kelley, A., Banker, M., Goodrich, J., Dolinoy, D., Burant, C., Domino, S., Smith, Y., Song, P. and Padmanabhan, V. (2019+). Early pregnancy exposure to endocrine disrupting chemical mixtures are associated with inflammatory changes in maternal and neonatal circulation. Scientific Reports (to appear).