The Statistics and Data Management Core-C provides to all Center investigators statistical consultation and collaboration on experimental design, statistical modeling and data analyses, and statistical support for preparing presentations and manuscripts. The Statistics and Data Management Core-C also maintains: (1) databases for the clinical, demographic and diagnostic data concerning psychiatric patients and control subjects for the Clinical Services and Diagnostics Core-B, as well as specific research data for Projects 4 and Project 5;and (2) databases for the Brain Tissue Donation Program and for animal post-mortem tissue data. In addition to these two major goals, the Statistics and Data Management Core-C develops novel statistical methodology to support the Center's research goals. The Statistics and Data Management Core- C's personnel include: (1) two senior faculty from the University of Pittsburgh's Department of Statistics, both of whom have substantial research experience in neurostatistics and statistical applications in psychiatry, as well as extensive publications on statistical methods;(2) senior database administrators and support staff with broad experience in managing databases for centers with many projects;and (3) Graduate Student Researchers (advanced Ph.D. students in the Department of Statistics) who support detailed data analyses. The two major areas of neuroscience statistical research that the Statistics and Data Management Core-C is pursuing involve clustering technologies and adaptive designs specific to center studies. The overarching goal of the clustering research is to develop methods which use post-mortem tissue study results or PET, EEC and fMRI clinical study results to attempt to identify possible clusters of schizophrenia subjects, and to characterize these clusters. The goal of the adaptive designs research is to provide novel adaptive statistical designs tailored for use in the Center's studies, including postmortem tissue studies, animal studies and clinical studies, with a purpose to increase design efficiency while maintaining design power. In summary, the Statistics and Data Management Core-C provides state-of-the-art statistical support to the Center's research projects and maintains secure and accurate databases for these projects, and conducts statistical research to identify biologically similar clusterings of schizophrenia and to develop new study designs which make more efficient use of resources.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Specialized Center (P50)
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Special Emphasis Panel (ZMH1-ERB-S)
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University of Pittsburgh
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Kimoto, Sohei; Glausier, Jill R; Fish, Kenneth N et al. (2016) Reciprocal Alterations in Regulator of G Protein Signaling 4 and microRNA16 in Schizophrenia. Schizophr Bull 42:396-405
Lewis, David A; Glausier, Jill R (2016) Alterations in Prefrontal Cortical Circuitry and Cognitive Dysfunction in Schizophrenia. Nebr Symp Motiv 63:31-75
Fromer, Menachem; Roussos, Panos; Sieberts, Solveig K et al. (2016) Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat Neurosci 19:1442-1453
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Teel, Chen; Park, Taeyoung; Sampson, Allan R (2015) EM Estimation for Finite Mixture Models with Known Mixture Component Size. Commun Stat Simul Comput 44:1545-1556
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Frankle, W Gordon; Cho, Raymond Y; Prasad, Konasale M et al. (2015) In vivo measurement of GABA transmission in healthy subjects and schizophrenia patients. Am J Psychiatry 172:1148-59
Hoftman, Gil D; Volk, David W; Bazmi, H Holly et al. (2015) Altered cortical expression of GABA-related genes in schizophrenia: illness progression vs developmental disturbance. Schizophr Bull 41:180-91
Cho, Raymond Y; Walker, Christopher P; Polizzotto, Nicola R et al. (2015) Development of sensory gamma oscillations and cross-frequency coupling from childhood to early adulthood. Cereb Cortex 25:1509-18

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