DecisionDrift 0.1.0
Initial release
Core modules
dd_build() — construct a drift_panel
object from long-format panel data.dd_prevalence() — detect drift in decision rate;
computes Decision Drift Index (DDI).dd_transition() — detect drift in transition structure;
computes Transition Drift Index (TDI).dd_entropy_trend() — track rolling Shannon entropy and
switching rate over time.dd_group_drift() — detect group-differential drift;
computes Group Differential Drift (GDD).dd_changepoint() — change-point and regime-shift
detection via CUSUM, segmented regression, and event alignment.
Summary indices
dd_indices() — compute all four original drift indices
in one call: DDI, TDI, GDD (Group Differential Drift), CDB (Cumulative
Drift Burden).
Robustness & sensitivity
dd_robustness() — test stability of drift conclusions
across analytic choices (balanced panel, leave-one-period-out,
leave-one-group-out, min_waves grid, bootstrap CI).dd_sensitivity() — probe vulnerability to data
problems: decision miscoding, missing-wave attrition, threshold shifts,
and subgroup composition shifts.
Flagship audit
dd_audit() — integrated three-layer audit (detection →
decomposition → stress-testing) with a single-call verdict.
Plotting
- S3
plot() methods for all module outputs.
- Multi-panel composite via
plot.dd_audit() (requires
patchwork).
Relationship to
decisionpaths
decisionpaths asks: What happened? (path
construction, DRI, entropy, equity)DecisionDrift asks: Did the system change?
(drift detection, decomposition, stress-testing)- These packages form complementary layers of a longitudinal decision
audit framework.