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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PSpower() function has been
replaced by power_ps() and power_cox(),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.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.