Code from: Calibrating P-values in ecology: A practical framework for integrating prior plausibility into statistical inference

This repository contains R code implementing the p‑value calibration method presented in the associated article. The core function, min_posterior, takes a p‑value and the prior probability of the alternative hypothesis and returns the minimum posterior probability of the null hypothesis, using a Bayes factor calibration based on Sellke et al. (2001). The code includes input checks, example calls for different prior plausibilities, and a short script to visualize how the minimum posterior probability of the null changes as a function of the p‑value for a given prior. This resource is intended as a practical implementation of the theoretical framework in the paper, allowing ecologists to translate conventional p‑values into calibrated measures of evidence that explicitly incorporate prior plausibility.
, , # Code from: Calibrating P-values in ecology: A practical framework for integrating prior plausibility into statistical inference

## Overview

This repository contains R code implementing the p-value calibration method introduced in the article: Guariento, R. D., Gripp, A., Caliman, A. (2026). *Calibrating P-values in ecology: a practical framework for integrating prior plausibility into statistical inference*. Oikos.

The main purpose of the code is to provide a practical tool for converting conventional p-values into minimum posterior probabilities of the null hypothesis, explicitly incorporating the prior plausibility of the alternative hypothesis.

## Contents

* `function_code.R`: R script defining the function `min_posterior` and example usage.

## Description of the function

`min_posterior(p, prior_alt)` computes the minimum posterior probability of the null hypothesis $$H_0$$ given:

* `p`: a p-value from a statistical test (0 < p < 1).
* `prior_alt`: the prior probability of ..., ,