A Spreadsheet for Deriving a Confidence Interval, Mechanistic Inference and Clinical Inference from a P Value (Report‪)‬

The null-hypothesis significance test based only on a p value can be a misleading approach to making an inference about the true (population or large-sample) value of an effect statistic. Inferences based directly on the uncertainty in the true magnitude of the statistic are more comprehensible and practical but are not provided by statistical packages. I present here a spreadsheet that uses the p value, the observed value of the effect and smallest substantial values for the effect to make two kinds of magnitude-based inference: mechanistic and clinical. For a mechanistic inference the spreadsheet shows the effect as unclear if the confidence interval, which represents uncertainty about the true value, overlaps values that are substantial in a positive and negative sense; the effect is otherwise characterized with a statement about the chance that it is trivial, positive or negative. For a clinical inference the effect is shown as unclear if its chance of benefit is at least promising but its risk of harm is unacceptable; the effect is otherwise characterized with a statement about the chance that it is trivial, beneficial or harmful. The spreadsheet allows the researcher to choose the level of confidence (default, 90%) for mechanistic inferences and the threshold chances of benefit (default, 25%) and harm (default, 0.5%) for clinical inferences. The spreadsheet can be used for the most common effect statistics: raw, percent and factor differences in means; ratios of rates, risks, odds, and standard deviations; and correlations. The calculations are based on the same assumption of a normal or t sampling distribution that underlies the calculation of the p value for these statistics. KEYWORDS: clinical decision, confidence limits, null-hypothesis test, practical importance, statistical significance. **********