Package Updates

Changes in Version 1.1.1 (TBD)

• Fixed a bug occuring when using custom outcome models in the gformula() function (Thanks to @Keling-Wang)

Changes in Version 1.1.0 (2024-09-30)

• Added a new approach for specifying interventions in the gformula() function. See the vignette “A Simplified Approach for Specifying Interventions in gfoRmula”.
• Added option for users to specify custom outcome models in the gformula() function. See the vignette “Using Custom Outcome Models in gfoRmula”.
• Added the option to not truncate covariates simulated from a normal distribution. See the argument sim_trunc to the gformula() function
• Fixed a bug occuring when using covariates of type "categorical time"
• Fixed an issue where the point estimates differed when changing the number of bootstrap samples. Since this fix involved adding a set.seed statement, point estimates can be numerically different from previous versions of the package.
• Added unit tests.

Changes in Version 1.0.4 (2024-01-30)

• Fixed an error for joint interventions on multiple treatments
• Fixed an error occurring when multiple restrictions are applied to a single variable
• Revised the gformula() function so that it produces a warning message rather than an error message when one of the bootstrap replicates fails. The bootstrap standard errors and 95% CIs are calculated based on the bootstrap replicates that do not fail.
• Fixed an error occurring when no interventions are supplied (i.e., only the natural course intervention is used)
• Slightly sped up the calculation of the counterfactual cumulative risks
• Expanded the error checking

Changes in Version 1.0.3 (2023-05-18)

• Fixed an error in the gformula() function that assumed that the name of the ID variable in obs_data was 'id'
• Removed Travis CI

Changes in Version 1.0.2 (2023-02-27)

• Revised the plot of the estimates of the natural course risk so that it starts at (0, 0)
• Fixed an error when obtaining confidence intervals around the hazard ratio estimates
• Fixed an error in the reported standard errors of the coefficients of the fitted categorical covariate models
• Fixed an error in the reported root mean squared error values for the outcome and competing event models
• Allowed categorical covariates to be of class “numeric” (rather than requiring them to be of class “factor”)

Changes in Version 1.0.1 (2023-01-11)

• Added the “cumulative percent intervened on” and “average percent intervened on” to the output of the gformula() function
• Added option for users to carry forward the natural value of treatment rather than the intervened value. See the int_visit_type argument in the gformula() function
• Added option for users to access the bootstrap replicates of the parametric g-formula estimates. See the boot_diag argument in the gformula() function.
• Fixed an error in computing the inverse probability weighted means of the time-varying covariates

Changes in Version 1.0.0 (2022-04-09)

• Added option for users to specify censoring models to compute inverse probability weights for estimating the natural course means / risk from the observed data
• Added data set censor_data and a corresponding example application in the documentation to illustrate the application of inverse probability weighting for estimating the natural course means / risk from the observed data
• Fixed an error in calculating the means of the time-varying covariates under the natural course for survival outcomes
• Fixed errors in calculating the observed risk estimates and g-formula survival estimates when competing events are not treated like censoring events
• For categorical time-varying covariates, the plot.gformula_survival(), gformula_continuous_eof(), and gformula_binary_eof() functions now display the nonparametric/IP weighted and parametric g-formula estimates of the probability of observing each level of the covariate. Previously, these functions displayed the counts of categorical variables.

Changes in Version 0.3.2 (2021-07-13)

• Updated computation of (lagged) cumulative averages to use the recursive formula. There should be a noticeable improvement in the computation time when using several (lagged) cumulative average terms and when the number of time points is large.
• Fixed an error for covariates of type truncated normal (Thanks to
• Updates to the documentation

Changes in Version 0.3.1 (2020-03-22)

• Fixed error in the coef.gformula() example

Changes in Version 0.3.0 (2020-01-30)

• Added wrapper function called gformula() for the gformula_survival(), gformula_continuous_eof(), and gformula_binary_eof() functions. Users should now use the more general gformula() function to apply the g-formula.
• Added option for users to specify the values for lags at pre-baseline times by including rows at time -1, -2, …, -i.
• Added an example data set called continuous_eofdata_pb, which illustrates how to prepare a data set with pre-baseline times
• Added option for users to pass in “control parameters” (e.g., maximum number of iterations, maxit, in glm.control) when fitting models for time-varying covariates via the covparams$control argument. (Thanks to @jerzEG for the suggestion)
• Added option for users to access the fitted models for the time-varying covariates, outcome, and competing event (if applicable). See model_fits argument of the gformula() function
• Added simulated data under the natural course to the sim_data component of the output of the gformula() function
• Added a progress bar for the number of bootstrap samples completed. See the show_progress argument of the gformula() function for further details
• Added summary(), coef(), and vcov() S3 methods for objects of class ‘gformula’
• Added argument fits in the print.gformula_survival(), print.gformula_continuous_eof(), and print.gformula_binary_eof() functions. Added argument all_times in the print.gformula_survival() function
• Fixed minor bug in the lagavg() function
• Fixed bug occuring when not using lags of the intervention variable(s)
• Fixed bug occuring in the truncation beyond covariate ranges. (Thanks to Louisa Smith)
• Updates to the documentation

Changes in Version 0.2.1 (2019-08-24)

• First version released on CRAN (https://CRAN.R-project.org/package=gfoRmula)
• Updates to the documentation

Changes in Version 0.2.0 (2019-08-22)

• Removed example_intervention1(), example_intervention2(), and visit_sum_orig(), as these functions are not used internally and users should not directly apply them
• Removed export of visit_sum() and natural(), as these functions are used internally and users should not directly apply them
• Updates to the documentation

Changes in Version 0.1.1 (2019-08-21)

• Minor updates to the documentation

Changes in Version 0.1.0 (2019-08-17)

• First version released on GitHub (https://github.com/CausalInference/gfoRmula)