Just one small additional note below ... Bert Gunter Genentech Nonclinical Biostatistics
"But a lot of academics are not going to "waste" their time documenting code properly, so others can reap the benefits of it. They would rather get on with the next project, to get the next paper. " -- Indeed. My personal experience over 3 decades in industrial (private) research is that data analysis is viewed as relatively unimportant/straightforward/pedestrian and is left to technicians (or postdocs) -- often with what is done being largely dictated by the conventions of a particular journal or discipline. The lab heads and research directors are responsible for the grand research strategies, managing resources, etc. and don't want to waste much time on something that routine. So worrying about reproducibility of data analysis "code" (if there is any, given the use of GUI software like Excel) falls beneath their radar. Clearly there are disciplines (e.g. ecology?) where this may NOT be the case. -- Bert ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
