Predicting the Significance of Necessity - Sorjonen, Kimmo; Melin, Bo (Frontiers in Psychology, 2019)
With Necessary Condition Analysis (NCA), a necessity effect is estimated by calculating the amount of empty space in the upper-left corner in a plot with a predictor X and an outcome Y, and recently a method for testing the statistical significance of the necessity effect through permutation has been proposed. In the present simulation study, this method was found to give significant results already with a very weak true population necessity effect, i.e. exhibit high power, unless the sample size is very small. However, in some situations the significance of the necessity effect tends to increase with increased degree of sufficiency, which is paradoxical for a method whose objective is to find necessary but not sufficient conditions.