Changes in version 0.2.0 (2026-01-10)                  

Breaking Changes

  - API Unification: Changed estimand parameter to weight_method in
    surveff() and marCoxph() for consistency across all package
    functions
    
      - estimand = "ATE" → weight_method = "IPW"
      - estimand = "overlap" → weight_method = "OW"
      - estimand = "ATT" → weight_method = "ATT" (name unchanged, but
        parameter name changed)

  - Changed trim parameter from character to logical in surveff(),
    marCoxph(), and weightedKM()
    
      - trim = "symmetric" → trim = TRUE
      - trim = NULL → trim = FALSE

  - Removed alpha parameter and asymmetric trimming support from all
    functions due to poor statistical performance in practice
    
      - Only symmetric trimming (Crump extension for multiple
        treatments) is now supported

  - Default delta is now NULL (automatic selection based on number of
    treatment groups) instead of a fixed value

New Features

  - New function: weightedKM() for weighted Kaplan-Meier estimation with
    propensity score weights
    
      - Supports IPW, overlap weights, ATT, and classical unweighted
        Kaplan-Meier
      - Uses classic weighted Greenwood variance formula
      - Handles binary and multiple treatment groups

  - New S3 methods for weightedKM objects:
    
      - plot.weightedKM(): Visualize weighted Kaplan-Meier or cumulative
        risk curves with confidence intervals
      - summary.weightedKM(): Tabular summaries with confidence
        intervals
      - print.weightedKM(): Formatted console output

  - Risk table support in plot.weightedKM():
    
      - Display number at risk and cumulative events below survival/risk
        curves
      - Customizable statistics, breaks, height, and font size
      - Automatic group name positioning and formatting

  - Enhanced visualization options:
    
      - Three confidence interval types: plain, log, log-log (default)
      - Cumulative risk plots (1 - survival)
      - Customizable colors, widths, transparency, and legends

Documentation

  - Unified weighting method descriptions across all main functions
    (surveff(), marCoxph(), weightedKM())
  - Added comprehensive @details sections explaining IPW, OW, and ATT
    weighting methods
  - Updated all examples to use new API with weight_method parameter

Internal

  - Moved ggplot2 and cowplot from Suggests to Imports (required for
    plotting functions)
  - Parameter mapping layer in surveff() and marCoxph() to transform
    user-facing API to internal implementation

Migration Guide for Existing Users

If upgrading from version 0.1.0:

  - Replace estimand = "ATE" with weight_method = "IPW"
  - Replace estimand = "overlap" with weight_method = "OW"
  - Replace estimand = "ATT" with weight_method = "ATT"
  - Replace trim = "symmetric", delta = 0.1 with trim = TRUE, delta
    = 0.1
  - Replace trim = NULL with trim = FALSE (or simply omit, as FALSE is
    default)
  - Remove alpha parameter entirely (asymmetric trimming no longer
    supported)
  - Set delta = NULL to use automatic defaults (0.1 for binary, 0.067
    for 3 groups, 1/(2J) for J ≥ 4)

Example migration:

# Old (v0.1.0)
result <- surveff(
  data = mydata,
  ps_formula = Z ~ X1 + X2,
  censoring_formula = Surv(time, event) ~ X1,
  estimand = "overlap",
  censoring_method = "weibull"
)

# New (v0.2.0)
result <- surveff(
  data = mydata,
  ps_formula = Z ~ X1 + X2,
  censoring_formula = Surv(time, event) ~ X1,
  weight_method = "OW",
  censoring_method = "weibull"
)

                 Changes in version 0.1.0 (2025-12-09)                  

  - Initial CRAN release

  - Documentation improvements for CRAN resubmission:
    
      - Added @return tags to print methods
      - Removed examples from internal functions
      - Updated examples to use \donttest{} with executable code
      - Enhanced output documentation for all exported functions

  - Implements propensity score weighting methods for estimating
    counterfactual survival functions and marginal hazard ratios in
    observational studies with time-to-event outcomes

  - Main functions:
    
      - surveff(): Estimates counterfactual survival curves and survival
        differences over time
      - marCoxph(): Estimates marginal hazard ratios via weighted Cox
        regression

  - Supports binary and multiple (>2) treatment groups

  - Weighting methods:
    
      - Inverse probability weighting (ATE)
      - Treated/target group weighting (ATT)
      - Overlap weighting

  - Propensity score trimming:
    
      - Symmetric trimming (Crump et al.)
      - Asymmetric trimming (Sturmer et al.)

  - Censoring adjustment methods:
    
      - Weibull accelerated failure time models
      - Cox proportional hazards models

  - Variance estimation:
    
      - Analytical M-estimation (binary treatment with Weibull
        censoring)
      - Bootstrap (all configurations, with full or stratified
        resampling)

  - Comprehensive documentation including vignette with examples

  - Based on methods from Cheng et al. (2022) doi:10.1093/aje/kwac043
    and Li & Li (2019) doi:10.1214/19-AOAS1282