Abstract Aging research studies are increasingly multidisciplinary in nature with longitudinal study design and extensive data collection including genomic, multi-omics, and large electronic medical records data in addition to traditional clinical data. These increased complexities in study design and data dimensionality present special challenges to aging researchers in data analyses and result interpretation for meaningful and reproducible scientific discoveries. I have conducted independent statistical research and have also collaborated extensively with investigators in aging research during my two-decades career at Indiana University School of Medicine. I have also mentored junior investigators on K-applications and directed Ph.D. students in research focused on statistical methods in aging research. The Academic Leadership Award will provide support for developing a comprehensive statistical training program that includes advanced statistical methods tailored to physicians and scientists in aging research and illustrated using case studies from aging research projects. The first aim is to develop an Advanced Statistical Methods in Aging Research curriculum that will provide comprehensive, in-depth training of modern statistical methods applicable to aging research. The second aim is to enhance research capacity at Indiana University by providing data resources and analytical tools from completed and ongoing aging studies to support secondary data analyses and pilot projects. The third aim is to provide individual mentoring to junior investigators for obtaining career development awards. A comprehensive, robust and advanced statistical training program will lead to better study design, increased research productivity, higher research quality and reproducible scientific discoveries in aging research.