Hypothesis Tests and P-Values

A blog article describing how to correctly interpret a “non-significant” p-value.

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What the article offers

This resource is a blog article intended to help readers avoid over-interpreting study results when the p-value of interest is not significant, which is one of the most common mistakes in clinical research.  To help readers understand that “not significantly different” doesn’t mean “the same”, it explains the proper way to show that two groups are similar with respect to an outcome.  Simple clinical research examples are used throughout.

Who created it

Thomas G. Stewart, PhD, Assistant Professor of Biostatistics, VICTR Research Methods Program at Vanderbilt University Medical Center