The Department of Biostatistics, the Department of Psychiatry, and the Biomedical Research Imaging Center at the University of North Carolina at Chapel Hill (UNC) propose a research training program in mental health biostatistics with an emphasis on neuroimaging and genomics that will support three predoctoral students and two postdoctoral scholars. The objective is to develop independent investigators, who are able to use a wide range of analytical approaches in biostatistics to answer important scientific questions in mental health research. The program is built upon existing collaborative relationships among biostatistics, mental health, radiology, computer science, and psychology research faculty in the Department of Biostatistics (BIOS), the Department of Statistics & Operation Research (STAT), the Department of Psychiatry (PSYCH), the Department of Radiology (RADIO), the Department of Genetics (GNET), the Department of Computer Science (CS), the Department of Psychology (PSY), and the Biomedical Research Imaging Center (BRIC). Training will usually be 2-3 years in duration for predoctoral students and postdoctoral/research scholars. The training program is designed to: (i) provide solid training of the biostatistical methods for mental health research; (i) provide broad expertise of mentors in biostatistics, radiology, genetics, psychology, and psychiatry; (iii) rotate trainees through different laboratories in psychiatry and psychology durin their training; and (iv) prepare trainees to pursue academic research careers in developing methods and collaborations needed in mental health research. Major strengths of the program include: (i) the prestigious training programs in biostatistics and psychiatry, including comprehensive courses on big data, genomics and neuroimaging methods available to trainees; (ii) the wide-ranging experience of the biostatistics, psychiatry, and psychology faculty in multiple areas of biostatistics methods and mental health research; (iii) a highly productive research environment in BIOS, STAT, PSYCH, RADIO, CS, PSY, GNET, and BRIC designed to support education and training in mental health biostatistics; (iv) access to a large number of mental health research projects in PSYCH, BIOS, BRIC, and PSY; (v) access to high throughput genetic and neuroimaging facilities; and (vi) the long history of successful research training programs offered by PSYCH and BIOS. The resources available to trainees include a broad array of ongoing mental health neuroimaging and genomics and biostatistics research projects; UNC-CH's commitment to collaborative research and training; and the broad range of expertise and experiences of faculty participating in this training program.
This multidisciplinary five-year program is designed to train predoctoral students (PhD) and postdoctoral scholars in two interrelated areas: Biostatistics and Mental Health Neuroimaging and Genomics. The goal is to prepare scientists to address emerging challenges in public health and medical research in mental health.
| Stephens, Rebecca L; Langworthy, Benjamin; Short, Sarah J et al. (2018) Verbal and nonverbal predictors of executive function in early childhood. J Cogn Dev 19:182-200 |
| Girault, Jessica B; Langworthy, Benjamin W; Goldman, Barbara D et al. (2018) The Predictive Value of Developmental Assessments at 1 and 2 for Intelligence Quotients at 6. Intelligence 68:58-65 |
| Risk, Benjamin B; Zhu, Hongtu (2018) Note on bias from averaging repeated measurements in heritability studies. Proc Natl Acad Sci U S A 115:E122 |
| Stephens, Rebecca L; Watson, Linda R; Crais, Elizabeth R et al. (2018) Infant quantitative risk for autism spectrum disorder predicts executive function in early childhood. Autism Res 11:1532-1541 |
| Cornea, Emil; Zhu, Hongtu; Kim, Peter et al. (2017) Regression Models on Riemannian Symmetric Spaces. J R Stat Soc Series B Stat Methodol 79:463-482 |
| Li, Jialiang; Huang, Chao; Zhu, Hongtu (2017) A Functional Varying-Coefficient Single-Index Model for Functional Response Data. J Am Stat Assoc 112:1169-1181 |
| Zhu, Wensheng; Yuan, Ying; Zhang, Jingwen et al. (2017) Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study. Neuroimage 146:983-1002 |
| Hyun, Jung Won; Li, Yimei; Huang, Chao et al. (2016) STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data. Neuroimage 134:550-562 |
| Luo, Xinchao; Zhu, Lixing; Zhu, Hongtu (2016) Single-index varying coefficient model for functional responses. Biometrics 72:1275-1284 |
| Shen, Dan; Shen, Haipeng; Zhu, Hongtu et al. (2016) The Statistics and Mathematics of High Dimension Low Sample Size Asymptotics. Stat Sin 26:1747-1770 |
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