Streamlining Study Design and Statistical Analysis

Introduction: Key factors causing irreproducibility of research include those related to inappropriate study design methodologies and statistical analysis; In modern statistical practice irreproducibility could arise due to; Statistical: False discoveries, p-Hacking, Overuse/misuse of p-values, Low power, Poor experimental design; Computational: Data, Code & Software management issues; These require understanding the processes and workflows practiced by an organization, and the development and use of metrics to quantify reproducibility. Conclusion: Automated platforms for statistical workflows; Data-intensive process use process-workflow management platforms: Activiti, Pegasus and Taverna; These strategies for sharing and publishing study protocols, data, code and results across the spectrum, active collaboration with the research team, automation of key steps, along with decision support will ensure quality of statistical methods and reproducibility of research.