CFAR Biostatistics Core (CBC) Dr. Mimi Kim, Director

Science at the heart of medicine Division of Biostatistics 14 Doctoral, 4 Associate Level Xiaonan Xue Wenzhu Bi Juan Lin Charles Hall Cuiling Wang Yiting Yu Yungtai Lo Kenny Ye Dan Wang Abdissa Negassa Tao Wang Sam Xie Hillel Cohen Moonseong Heo Ryung Kim Shankar Viswanathan Mimi Kim Baiyu Zhou 5 Professors, 4 Associate Professors, 5 Assistant Professors

Science at the heart of medicine Organization Division of Biostatistics CFAR Biostatistics Core AECC Biostatistics Shared Resource ICTR Biostatistics Core EAS Biostatistics Core Center for Quantitative Sciences

Why do we need the CBC? Access to statisticians experienced in HIV/AIDS Research Increase in statistical personnel available to CFAR investigators Wider range of expertise

Personnel in CBC Einstein campus: Mimi Kim, Director (15% FTE) Yungtai Lo, Doctoral level statistician (10% FTE) Juan Lin, Masters level statistician (20% FTE) Montefiore campus: Moonseong Heo, Associate Director (26% FTE) Yuming Ning, Doctoral level statistician (45% FTE)

Areas of expertise Laboratory experiments Clinical trials Epidemiologic studies Longitudinal and clustered data Mixture models Missing data Genetics/Genomics

Specific Aims Provide statistical and epidemiologic support on all phases of HIV/AIDS research studies Provide support for new HIV/AIDS-related research initiatives Identify new problems requiring the development of novel statistical methods Provide training and mentoring in research methodology

Aim 1: Support on all phases of AIDS research Study design (lab experiments, genomics and genetics studies, clinical trials, epi studies) Study conduct and monitoring Data presentation, analysis, interpretation, reporting

Aim 2: Support on new research initiatives Development of protocols and applications for peer-reviewed funding Formulation of hypotheses Sample size calculations Analytic plan

Aim 3: Methods Development Identify issues in AIDS research which need new methodological development Center for Quantitative Sciences in Biomedical Research

Aim 4: Training and Mentoring Examples : Biostatistics and Study Design: Identifying and Avoiding Common Errors Statistical methods in comparative effectiveness research Meta-analysis Current approaches for adjusting for confounding in observational studies Microarray data pre-processing and normalization, methylation analysis, DNA sequence analysis.

Policies No charge for short-term statistical support No charge for grant proposals but statistical collaborator should be included in the budget for appropriate % FTE Authorship: based on contribution to paper and independent of whether funding was received

Resubmission Need to identify stat/epi needs in other cores and CBC link to each core -Clinical and Translational Investigation Core (M.Heo; Y. Ning) -Flow Cytometry Core (J. Lin) -Virology Core (Y. Lo) -Immunology/Pathology Core (Y. Lo) -Animal Biohazard Core (J. Lin) -Developmental Core (M. Kim)

Better coordination of CBC write-up with other cores Identify areas in AIDS research which need new methods development Ideas for short course/training topics for CFAR members