title: Logical Experimental Design and Execution in the Biomedical Sciences.
abstract: Lack of reproducibility has been highlighted as a significant problem in biomedical research. The present unit is devoted to describing ways to help ensure that research findings can be replicated by others, with a focus on the design and execution of laboratory experiments. Essential components for this include clearly defining the question being asked, using available information or information from pilot studies to aid in the design the experiment, and choosing manipulations under a logical framework based on Mill's "methods of knowing" to build confidence in putative causal links. Final experimental design requires systematic attention to detail, including the choice of controls, sample selection, blinding to avoid bias, and the use of power analysis to determine the sample size. Execution of the experiment is done with care to ensure that the independent variables are controlled and the measurements of the dependent variables are accurate. While there are always differences among laboratories with respect to technical expertise, equipment, and suppliers, execution of the steps itemized in this unit will ensure well-designed and well-executed experiments to answer any question in biomedical research. © 2017 by John Wiley & Sons, Inc.
authors.affiliation: Biometrics Research, Merck Research Laboratories, West Point, Pennsylvania.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Holder
authors.affiliation: Neuroscience, Merck Research Laboratories, West Point, Pennsylvania.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Marino
mesh_terms: D000818:Animals; D035843:Biomedical Research / Q000379:methods*; D015984:Causality; D004195:Disease Models, Animal; D006801:Humans; D010600:Pharmacology / Q000379:methods*; D010865:Pilot Projects; D015203:Reproducibility of Results; D012107:Research Design
keywords: causality; experimental controls; experimental design; experimental execution; power analysis