This is a major revision with a fully rewritten codebase, new theoretical foundations, and substantially expanded functionality. The API is not backward-compatible with version 0.1.1.
power_ps() — sample size and power for the
PS-weighted Hájek estimator with continuous or binary outcomes. Supports
four estimands (ATE, ATT, ATC, ATO) via closed-form (ATE) or numerical
integration (ATT, ATC, ATO, custom tilting functions). Accounts for the
confounder coefficient ρ² and the Bhattacharyya overlap coefficient
φ.
power_cox() — sample size and power for the
PS-weighted partial likelihood estimator in a Cox proportional hazards
model with time-to-event outcomes. Supports randomized trials (robust
sandwich variance or Schoenfeld formula) and observational studies (ATE
via IPW; ATO and ATT via Monte Carlo design-effect adjustment).
overlap_coef() — estimates the Bhattacharyya overlap
coefficient φ from fitted propensity scores and a treatment indicator,
or analytically from Beta distribution parameters.
S3 print(), summary(), and
plot() methods for both power_ps and
power_cox result objects. Scalar inputs produce a formatted
single-scenario summary; vector inputs produce a multi-scenario grid
with a five-number distribution summary and a ggplot2-based
sensitivity plot.
PSpower() function has been
replaced by power_ps() and power_cox(),
covering a broader set of estimands and outcome types.
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