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.
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