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.

Design support and interface

• 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.”

Data generation

• 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.

Documentation and maintenance

• 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.

sreg 2.0.2

sreg 2.0.1

• 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.

sreg 1.0.1.9000 (development version)

• Ongoing development version.

sreg 1.0.1

• 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.

sreg 1.0.0

• Initial CRAN release.