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simglm 1.0.0

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

• Small maintenance fix for incoming 0.8 dplyr.

simglm 0.7.1

• 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

• 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

• 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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.