NEWS

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simglm 1.0.0 (2026-09-01)

This major release accompanies the publication of the simglm book. It expands the package's simulation and power-analysis capabilities and aligns the package API with the examples presented in the book.

New outcome and data-generation options

• Added support for ordinal and multinomial outcomes.
• Added floor and ceiling controls for continuous outcomes.
• Changed factor simulation to preserve the declared order of levels rather than sorting levels alphabetically.
• Added force_equal = TRUE for generating equally represented factor levels.
• Expanded support for unbalanced designs and flexible sample-size specifications.
• Generalized cross-classified data generation through multiple-membership simulation.
• Added post-processing and outcome aggregation tools.
• Extended formula parsing and simulation support for list-based specifications and multiple-equation workflows.

Power analysis and model fitting

• Reworked the power-simulation framework, including improved support for between- and within-subject designs.
• Added type S and type M error summaries.
• Added robust_model() for models using robust standard errors.

Propensity score workflows

• Added simulate_propensity() for generating non-random treatment assignment.
• Added fit_propensity() and support for covariate adjustment, inverse probability weighting (ipw), and stabilized balancing weights (sbw).
• Added support, examples, and tests for multilevel propensity score designs.

Documentation, testing, and maintenance

• Expanded the vignettes and documentation for missing-data, factor, ordinal, multinomial, post-processing, power, and propensity score workflows.
• Added lightweight compatibility tests based on code published in the book.
• The package now requires R 4.1.0 or later because examples and simulation workflows use the native R pipe (|>)
• Removed Matrix from package imports and added gtools, sandwich, and lmtest.

simglm 0.7.2 (2019-01-23)

• Small maintenance fix for incoming 0.8 dplyr.

simglm 0.7.1 (2018-07-25)

• Release for new tidy simulation framework
• New vignettes showing this functionality

simglm 0.6.3

• Add piecewise linear simulation.

simglm 0.6.2

• Add cross classified model simulation
• Add option to specify any model to fit for power analysis
  • This brought about a change to use broom::tidy.

simglm 0.6.1

• Generalize fact_vars code
  • This now is similar to cov_param

simglm 0.6.0 (2017-07-24)

• Shiny Application works again!
  • Can now simulate and run power.
  • Able to download simulation and power tables (I think).

simglm 0.5.3

• Fixed basic functionality of Shiny application
  • This includes simulation and power
    • Needs more testing at this stage.

simglm 0.5.2

• Addition of count outcome from sim_glm.
  • This added an additional argument that must be specified:
    • outcome_type = 'logistic' = 0/1 dichotomous simulation
    • outcome_type = 'poisson' = count outcomes.

simglm 0.5.1

• Bug fix for sim_glm when using fact_vars generation options.

simglm 0.5.0 (2017-05-25)

• Heterogeneity of variance simulation
• Flexible time specification for longitudinal models
• Change 'lvl' to 'level' throughout package
• Flexible specification of unbalanced simulation
• Misspecification of model for power analysis
• Expand power output.

simglm 0.4.0

• Update to add ability to simulate covariates from any R distribution function
  • Old code will no longer work with this new version.
  • Added new opts argument to cov_param for optional distribution arguments.
• Adjusted vignettes to follow new code
• Adjusted unit tests.
• Added documentation for changes, including in vignettes.

simglm 0.3.4

• Added a NEWS.md file to track changes to the package.