Tag Archives: Research design

Recommended: The Importance of Reproducible Research in High-Throughput Biology

I have not viewed this video yet, but have attended a similar talk and read a similar research paper by Keith Baggerly. His general message is that large biological and genetic experiments are sometimes designed so poorly as to invalidate the results. You can often discover these design flaws through a careful examination of the data sets themselves and their metadata. This process of uncovering design flaws is sometimes called “Forensic Statistics.” Continue reading

PMean: How detailed should I make my data analysis plan.

Dear Professor Mean, I could use some advice on defining and following analysis plans for research proposals. I can see how in well-trodden research, where the nuances of the data are well understood, and reasonable distributional assumptions are already identified, a detailed analysis plan may be straightforward to develop. But what about cases where you collect observational data, and though you may have specific hypotheses in mind prior to collecting it, you can’t really pin down the most appropriate analysis until after you’ve done some exploration? Is there generally an acceptable amount of leeway in cases like these, where your analysis doesn’t follow the original plan to the dot, but it’s still designed to address the same question? Or must one be as specific and detailed in the plan as possible, and consider every contingency (e.g., if the distribution is noisy, switch to this non-parametric test)? Or does it really vary with whoever the reviewer is? Continue reading

PMean: How many months should you wait before re-testing?

I got a question that I had never heard before, and it sort of is a statistics question and sort of isn’t. A researcher was comparing two methods of training residents in a particular surgical procedure and wanted to know how long you should wait between the training and the evaluation of whether that training was effective. Continue reading