Potential pitfalls of experimental design
Phillip Watkins MS
Good experimental design begins with the end in mind. An early conversation with a statistician will both increase the chances of an experimental study contributing to the literature and minimize the risks to participating human subjects. Sir R.A. Fisher felt that “to consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination: he can perhaps say what the experiment died of.” To this end, some questions from a statistician are presented along with the associated experimental study pitfalls to avoid during the study planning phase. Several concrete examples are provided to give some practical knowledge on how to improve an experimental study at the onset. Hypothesis formulation, sample size determination, randomization, and double-blinding are all explained from the viewpoint of a statistician’s final analysis. Confounders, sampling, and missing data are also briefly covered through this hypothetical question and answer session.
Keywords: Experimental design, hypothesis formulation, sample size, randomization
Article citation: Watkins P. Potential Pitfalls of Experimental Design. Southwest Respiratory and Critical Care Chronicles 2017;5(17):68-70.
Author Affiliation: Phillip Watkins is a statistician who works in the Clinical Research Institute at Texas Tech University Health Sciences Center in Lubbock, TX.
Corresponding author: Phillip Watkins at Phillip.email@example.com
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