3 research outputs found
Make Research Data Public? -- Not Always so Simple: A Dialogue for Statisticians and Science Editors
Putting data into the public domain is not the same thing as making those
data accessible for intelligent analysis. A distinguished group of editors and
experts who were already engaged in one way or another with the issues inherent
in making research data public came together with statisticians to initiate a
dialogue about policies and practicalities of requiring published research to
be accompanied by publication of the research data. This dialogue carried
beyond the broad issues of the advisability, the intellectual integrity, the
scientific exigencies to the relevance of these issues to statistics as a
discipline and the relevance of statistics, from inference to modeling to data
exploration, to science and social science policies on these issues.Comment: Published in at http://dx.doi.org/10.1214/10-STS320 the Statistical
Science (http://www.imstat.org/sts/) by the Institute of Mathematical
Statistics (http://www.imstat.org
A call for transparent reporting to optimize the predictive value of preclinical research
The US National Institute of Neurological Disorders and Stroke convened major stakeholders in June 2012 to discuss how to improve the methodological reporting of animal studies in grant applications and publications. The main workshop recommendation is that at a minimum studies should report on sample-size estimation, whether and how animals were randomized, whether investigators were blind to the treatment, and the handling of data. We recognize that achieving a meaningful improvement in the quality of reporting will require a concerted effort by investigators, reviewers, funding agencies and journal editors. Requiring better reporting of animal studies will raise awareness of the importance of rigorous study design to accelerate scientific progress