NEWS

NonlinearDiD 0.2.0 (2026-05-20)

Added support for repeated cross-section staggered DiD designs.
Added data_type = "panel" and data_type = "repeated_cross_section" options.
Made idname optional for repeated cross-section designs.
Added support for sampling weights through weightsname.
Added support for clustered inference through cluster_var.
Added examples for binary repeated cross-section outcomes with staggered treatment timing.
Preserved all panel-data functionality from version 0.1.0.

Repeated cross-section ATT(g,t) uses the Wooldridge (2023) pooled QMLE with a treatment-by-period interaction. The doubly-robust variant augments this with inverse probability weighting on the estimated propensity score.
Sampling weights (when supplied via weightsname) are used throughout: the outcome regression, the propensity score model, and the pooled QMLE. They are multiplied with the IPW factor in the doubly-robust path.
Analytical SEs for the RCS path use sandwich::vcovCL when cluster_var is supplied, sandwich::vcovHC (HC1) otherwise. Panel SEs continue to use the influence-function approach from v0.1.0; set boot = TRUE for fully clustered panel inference.
The bootstrap automatically resamples whole clusters when cluster_var is provided, units when data_type = "panel", or individual rows when data_type = "repeated_cross_section" without clustering.
The compiled C++ helpers from v0.1.0 have been replaced with equivalent pure-R implementations, eliminating the Rcpp dependency. The package no longer requires compilation.

Initial CRAN release.
Panel-data ATT(g,t) estimation under logit, probit, Poisson, negative binomial, and linear outcome models.
Doubly-robust estimator combining outcome regression and propensity score weighting.
nonlinear_aggte(): event-study, group, calendar, and simple aggregations.
nonlinear_pretest(): joint chi-squared and individual pre-trend tests.
nonlinear_bounds(): Manski and parallel-trends-constrained bounds.
binary_did_logit(), binary_did_probit(), binary_did_dr(): 2x2 binary DiD estimators.
count_did_poisson(): Poisson QMLE DiD.
odds_ratio_did(): scale-free odds-ratio DiD.
sim_binary_panel(), sim_count_panel(): simulation utilities.