NEWS
gfoRmula 1.1.0 (2024-10-01)
- 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.
gfoRmula 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
gfoRmula 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
gfoRmula 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”)
gfoRmula 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
gfoRmula 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.
gfoRmula 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
@publichealthstudent)
- Updates to the documentation
gfoRmula 0.3.1 (2020-03-23)
- Fixed error in the
coef.gformula() example
gfoRmula 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
gfoRmula 0.2.1 (2019-08-25)
gfoRmula 0.2.0
- 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
gfoRmula 0.1.1
- Minor updates to the documentation
gfoRmula 0.1.0