Biostatistics, Computation and Data Management Core

Biostatistics, Computation and Data Management Core

Personnel

Hal Stern
Ted and Janice Smith Family Foundation Dean
and Professor of Statistics

Michael Phelan
Interim Director, UC Irvine Center Center for Statistical Consulting

Brian Vegetabile
Graduate Student, Department of Statistics

Core Aims

Aim 1: Develop and apply novel approaches to characterizing fragmentation and unpredictability of early-life experiences, enhancing the innovation of the Center’s research.

Aim 2: Provide data management services to all projects, and facilitate integration across projects. This includes setting up databases that can accommodate the range of data collected, and providing methods of integration of these datasets.

Aim 3: Provide biostatistical support for animal and human studies of the relationship between fragmentation and unpredictability of early-life experience and emotional, cognitive and imaging outcomes. Address potential confounders and optimize statistical approaches to the analysis of complex data-sets. This will enhance the impact of the Center project by optimizing the Center’s approaches.

Illustration of recurring sequences of behavioral events identified from a simulated behavioral observation.

Illustration of recurring sequences of behavioral events identified from a simulated behavioral observation.

Project Publications
  • Molet, J., Heins, K., Zhuo, X., Mei, Y.T., Regev, L., Baram, T.Z., and Stern, H. (2016) “Fragmentation and High Entropy of Neonatal Experience Predict Adolescent Emotional Outcome,” Translational Psychiatry (2016) 6, e702; (published online 5 January 2016)
  • Stern, H. S. (2016) “A Test by Any Other Name: P values, Bayes Factors and Statistical Inference”, Multivariate Behavioral Research, 51:1, 23-29.
  • (submitted) Glynn, Sandman, Davis, Phelan, Baram, Stern – Patterns of Prenatal Maternal Mood Predict Child Mental Health – submitted to JAMA
  • Heins, KA and Stern, HS (2014) “A Statistical Model for Event Sequence Data,” in Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS 2014), pp. 338-346.
  • Stern, H. (2014) Comment on “The Need for More Emphasis on Prediction: A “Nondenominational” Model-Based Approach” by D. A. Harville, The American Statistician, Vol. 68, No. 2, pp 83-84.
  • Stern, H. (to appear) “A Test By Any Other Name: P-values, Bayes Factors and Statistical Inference,” to appear in Multivariate Behavioral Research.
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