TITLE: Reproducible Research: Many Dimensions and Shared Responsibilities
DATE: Monday, March 14, 2016 – 11:30a – 1:30p (PDT)
VIDEOCAST: This workshop will be videocast.
INSTRUCTOR: Lisa Meier McShane, Ph.D., Chief, Biostatistics Branch, Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute
REGISTRATION: Not required.
WORKSHOP DESCRIPTION: Biomedical researchers have an ethical responsibility to ensure the reproducibility and integrity of their work, so that precious research resources are not wasted and, most importantly, flawed or misleading results do not make their way to clinical studies where the faulty evidence could adversely affect study participants. Many factors have been suggested as contributors to irreproducible biomedical research, including poor study design, analytic instability of measurement methods, sloppy data handling, inappropriate and misleading statistical analysis methods, improper reporting or interpretation of results, and, on rare occasions, outright scientific misconduct. These problems can occur in any type of biomedical study, whether preclinical or clinical, large or small. Examples of the many potential pitfalls will be discussed along with suggested approaches to avoid them. The first half of the seminar will focus mainly on issues that arise commonly in preclinical and small clinical studies or studies performed retrospectively using stored biospecimens. The second half will elaborate on aspects that are particularly problematic in research involving the use of novel measurement technologies such as “omics assays” which generate large volumes of data and require specialized expertise and computational approaches for proper data analysis and interpretation. The discussions will emphasize the importance of including in a research team all individuals with the needed expertise as early as possible in a project in order to promote a sense of engagement and facilitate good communication across disciplines. Shared credit for scientific accomplishments should be understood as an acceptance of shared accountability for the integrity of the work.
This lecture is part of a full day of scheduled events and activities for the second annual NIH Pi Day, which celebrates the intersection between the quantitative and biomedical sciences. Pi Day is an annual international celebration of the irrational number Pi, 3.14…, on March 14. On Pi Day and every day, NIH recognizes the importance of building a diverse biomedical workforce with the quantitative skills required to tackle future challenges.