The Statistics and Data Management Core (Stats/DM Core) 1) provides statistical support to investigators conducting Center research studies and 2) maintains the databases required by projects. Core and Project investigators collaborate on experimental design, statistical modeling and analyses, and statistical graphics and presentations in Projects 1-5. These capabilities include design support ranging from broad conceptual support to detailed power calculations;analytic support ranging from advice on appropriate statistical models to conducting complex statistical analyses;and presentation support ranging from graphical advice to co- authoring papers and abstracts. In addition, the Stats/DM Core will develop new statistical methodology to enhance the research conducted in the Center, and provide training opportunities for graduate students in statistics and all levels of trainees in neuroscience and psychiatric research. The Stats/DM Core data manager will work with the Department of Psychiatry's Office of Academic Computing and Center investigators to develop databases that facilitate the integration of results across projects (e.g., organized and retrievable databases for mRNA, miRNA, functional annotation and regulatory network data from P1&P3). The Stats/DM Core's statistical support will be provided by Dr. Allan Sampson (Core Director), and Drs. Kehui Chen and George C. Tseng (Core Co-Investigators). Consultative support will be available from Dr. Satish Iyengar and Dr. Lisa Weissfeld. Senior PhD Graduate Student Researchers will also provide detailed computations and analyses under the supervison of Core faculty. When projects could benefit from access to additional statistical expertise from the greater Pittsburgh statistical community, including other departments at the University of Pittsburgh and Carnegie-Mellon University, the Stats/DM Core will serve as a referral and coordination resource for Center investigators.
This Core will develop innovative statistical methodology when currently available statistical methods are not fully effective. New statistical methodology could provide advances beyond current statistical methods that can be utilized in other areas of translational mental health research, in addition to increasing the impact of studies conducted by Center investigators.
|Asafu-Adjei, Josephine K; Sampson, Allan R (2018) Covariate adjusted classification trees. Biostatistics 19:42-53|
|Chung, Daniel W; Chung, Youjin; Bazmi, H Holly et al. (2018) Altered ErbB4 splicing and cortical parvalbumin interneuron dysfunction in schizophrenia and mood disorders. Neuropsychopharmacology 43:2478-2486|
|Enwright Iii, J F; Huo, Z; Arion, D et al. (2018) Transcriptome alterations of prefrontal cortical parvalbumin neurons in schizophrenia. Mol Psychiatry 23:1606-1613|
|Huang, Ge; Ramachandran, Suchitra; Lee, Tai Sing et al. (2018) Neural Correlate of Visual Familiarity in Macaque Area V2. J Neurosci 38:8967-8975|
|Coffman, Brian A; Haigh, Sarah M; Murphy, Timothy K et al. (2018) Reduced auditory segmentation potentials in first-episode schizophrenia. Schizophr Res 195:421-427|
|Pafundo, Diego E; Miyamae, Takeaki; Lewis, David A et al. (2018) Presynaptic Effects of N-Methyl-D-Aspartate Receptors Enhance Parvalbumin Cell-Mediated Inhibition of Pyramidal Cells in Mouse Prefrontal Cortex. Biol Psychiatry 84:460-470|
|Hoftman, Gil D; Dienel, Samuel J; Bazmi, Holly H et al. (2018) Altered Gradients of Glutamate and Gamma-Aminobutyric Acid Transcripts in the Cortical Visuospatial Working Memory Network in Schizophrenia. Biol Psychiatry 83:670-679|
|Dorph-Petersen, Karl-Anton; Lewis, David A (2017) Postmortem structural studies of the thalamus in schizophrenia. Schizophr Res 180:28-35|
|Glausier, Jill R; Lewis, David A (2017) GABA and schizophrenia: Where we stand and where we need to go. Schizophr Res 181:2-3|
|Rocco, Brad R; DeDionisio, Adam M; Lewis, David A et al. (2017) Alterations in a Unique Class of Cortical Chandelier Cell Axon Cartridges in Schizophrenia. Biol Psychiatry 82:40-48|
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