
The American Society for Pharmacology and Experimental Therapeutics has revised the Instructions to Authors for Drug Metabolism and Disposition, Journal of Pharmacology and Experimental Therapeutics, and Molecular Pharmacology These revisions relate to data analysis (including statistical analysis) and reporting but do not tell investigators how to design and perform their experiments. Their overall focus is on greater granularity in the description of what has been done and found. Key recommendations include the need to differentiate between preplanned, hypothesis-testing, and exploratory experiments or studies; explanations of whether key elements of study design, such as sample size and choice of specific statistical tests, had been specified before any data were obtained or adapted thereafter; and explanation of whether any outliers (data points or entire experiments) were eliminated and when the rules for doing so had been defined. Variability should be described by S.D. or interquartile range, and precision should be described by confidence intervals; S.E. should not be used. P values should be used sparingly; in most cases, reporting differences or ratios (effect sizes) with their confidence intervals will be preferred. Depiction of data in figures should provide as much granularity as possible, e.g., by replacing bar graphs with scatter plots wherever feasible and violin or box-and-whisker plots when not. This editorial explains the revisions and the underlying scientific rationale. We believe that these revised guidelines will lead to a less biased and more transparent reporting of research findings.
Data Analysis, Publishing, Peer Review, Research, Pharmacology, Societies, Scientific, Biomedical Research, Drug Evaluation, Preclinical, Guidelines as Topic, Biostatistics, United States, Research Design, Data Interpretation, Statistical, Practice Guidelines as Topic, Humans, Periodicals as Topic, Editorial Policies
Data Analysis, Publishing, Peer Review, Research, Pharmacology, Societies, Scientific, Biomedical Research, Drug Evaluation, Preclinical, Guidelines as Topic, Biostatistics, United States, Research Design, Data Interpretation, Statistical, Practice Guidelines as Topic, Humans, Periodicals as Topic, Editorial Policies
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