sreg 2.1.0

Estimation and inference

Corrected the large-strata variance estimator for experiments with multiple active treatment arms under both individual- and cluster-level assignment. The estimator now includes the contribution of clusters or individuals assigned to active arms other than the arm being compared with control.
Corrected the small-strata cluster estimator. Point estimation now uses expanded cluster outcomes, cluster-level covariate means, and normalization by the mean represented cluster size. The corresponding variance estimator now incorporates the common random denominator and the contributions of all treatment arms.
Corrected mixed-design inference under cluster-level assignment. Component estimates are now weighted by their shares of the represented individual population, computed from Ng, and the variance estimator includes the variability of these random population shares.
Covariates supplied for a mixed design are now used in both its small- and large-strata components for individual- and cluster-level assignment. A targeted error explains when the large-strata component cannot identify the requested treatment-by-stratum adjustment and recommends reducing the covariate set or using X = NULL.
Improved HC1 handling in degenerate multi-treatment settings by reverting to the unadjusted variance estimate when the finite-sample correction is undefined.

Added the optional k argument to sreg(). It validates the common stratum size in uniform small-strata designs and identifies the small-stratum size in general mixed designs, extending mixed-design support beyond matched pairs and triplets to general k-tuples.
Improved automatic design classification, validation messages, and warnings for small- and mixed-strata designs under both individual- and cluster-level assignment.
Standardized user-facing output to use the term “large strata” rather than “big strata.”

Extended sreg.rgen() to generate mixed designs through the new mixed.strata and n.small arguments for both individual- and cluster-level assignment.
Added optional stratum-specific allocation probabilities, stratum effects, and treatment effects through allocation.probs, stratum.effects, and treatment.effects.by.stratum for large-strata individual-level designs.
Clarified that n counts clusters when cluster = TRUE, strengthened input validation, and corrected large-strata cluster generation so that is.cov = FALSE no longer returns covariate columns.

Substantially expanded the function documentation, examples, README, and introductory vignette to cover large-, small-, mixed-, and cluster-randomized designs and the S3 print and plot methods.
Corrected references and documented the structure of returned objects, cluster-size handling, cluster-level covariate aggregation, and mixed-design adjustment behavior.
Expanded the automated test suite for multi-arm variance estimation, general k-tuple and mixed designs, cluster estimators, data generation, design classification, and adjustment diagnostics.

CRAN release of the first stable version of sreg 2.0 # sreg 2.0.0
Major redesign of the package to support small strata designs (e.g., matched pairs and n-tuples), including correct estimators under both individual-level and cluster-level treatment assignment.
Added full support for mixed designs combining small and large strata, with appropriate estimators implemented.
Introduced a new S3 plot method (plot.sreg) for visualizing estimated treatment effects and confidence intervals for objects of class sreg.
Multiple bug fixes and internal improvements for stability and consistency.

Fixed a bug in the sreg function that caused it to return output for the unadjusted estimator instead of the adjusted estimator when X contained a single covariate.
Minor improvements and bug fixes.