Package Updates
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)
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)