SCAtools - Direction-Aware Sufficient Condition Analysis
Tests whether a high or low level of a condition is enough
to guarantee a high or low level of an outcome. Such a claim
predicts that one corner of the condition-outcome scatter plot
is empty of observations. The package estimates the boundary of
that empty corner, its size as a share of the scope (the effect
size), a permutation test against random pairing, and a
threshold table giving the condition level that guarantees each
outcome level, in actual units, percentages, percentiles or
standard deviations. Each of the four directions (high or low
condition, high or low outcome) is stated as a claim and mapped
to its empty corner. Because a condition can rule out low
outcomes while barely moving the average, results can be set
beside ordinary least-squares and median regression slopes,
showing whether the data hold an average effect, a sufficiency
effect or both. Also provides plots, influential-case
diagnostics, scope-sensitivity and resampling checks,
random-data generation and power analysis for planning studies.
Frontiers are estimated with the 'NCA' package.
