NaN,
resulting in an error.confint()
would print intervals for dose-related parameters only.
confint() now prints intervals for all parameters.Surv(entry, exit, status). ameras() now checks
the observed entry and exit time values and errors when any subject has
entry > exit.strata() terms that use a matched set column name other
than setnr.rmvnorm() error. Such realizations are now excluded with a
warning before FMA weights and samples are computed.included.realizations.BMA
leaves fewer than two dose realizations, since one-realization analyses
should use RC.entry == exit, which have zero follow-up time under the
entry < t <= exit risk-set convention.NA with diagnostic warnings
when a bound cannot be reliably solved.modifier = ~ M for reference-plus-contrast coding and
modifier = ~ 0 + M or modifier = ~ M - 1 for
subgroup-specific dose-effect parameters. Formula modifiers support
binary numeric/logical variables and factors with treatment coding based
on the factor level order. The older modifier = M1 + M2
syntax is deprecated.ameras() now supports a na.action argument
for model-input missing values after formula terms have been expanded.
By default it follows getOption("na.action") (typically
na.omit), stores the omitted-row action on the fitted
object, and reapplies the same policy when data are supplied later for
objects fitted with keep.data=FALSE. na.fail
and na.pass are also supported. na.exclude is
accepted for fitting, but residuals and diagnostic plots are returned
for the fitted rows rather than padded back to the originally supplied
row count.future
framework via future.apply when available. Users can enable
parallel execution by setting a future plan before calling
ameras(), and future.chunk.size.FMA controls
the chunk size passed to
future.apply::future_lapply().splines::ns() and
splines::bs(). For keep.data=FALSE fits, later
calls that use supplied data apply the same expanded covariate columns
as the original fit.convergence() for amerasfit objects
to extract or recompute optimizer gradient diagnostics for RC, ERC, and
MCML fits.dose_lrt() for global and individual
likelihood-ratio tests of dose-related parameters in RC, ERC, and MCML
fits.future framework.optim() reports convergence but optimizer diagnostics
suggest the solution may not be fully stationary. When the Hessian is
usable, the optimizer warning uses the approximate remaining objective
improvement on both absolute and relative scales.summary() now reports row counts in the order applied
during fitting: supplied rows, nonzero omissions by
na.action, nonzero family-specific exclusions, and rows
used for fitting when this differs from the supplied row count. For
conditional logistic regression, it reports rows excluded because they
belong to uninformative matched sets. For proportional hazards
regression with entry times, it reports rows excluded because they have
zero follow-up time.summary() and
confint(): columns pval.lower and
pval.upper for profile likelihood intervals are no longer
printed. They are still accessible within the fit object, and warnings
are still printed in case an inaccurate profile likelihood bound is
suspected.runtime
field is retained as a compatibility summary and is updated when
confint() adds confidence interval timing.rcdose_ameras.inpar check in
ameras() to generate an error when it should not.NULL for generated samples when all individual fits were
excluded.keep.data=FALSE and
passing data to confint() failed a validation check when
effect modifiers were present.isSymmetric check for FMA variance
matrices, which caused platform-dependent differences in included
realizations due to numerical differences between Cholesky and
solve-based computations. The Cholesky-based variance
computation now used guarantees exact symmetry without an explicit
check.confint() no longer recomputes confidence intervals by
default if they have already been computed. Use force=TRUE
to recompute with different settings. confint() now also
prints the computed confidence intervals when called with
print=TRUE (default).vcov, computed from the model-averaged posterior
samples.dosevars variable defined
locally (e.g., within a simulation script) through
all_of(dosevars) in the formula passed to
ameras().residuals(): computes Pearson, deviance, and response
residuals for all supported families, and Schoenfeld residuals for
family="prophaz", supporting both raw and scaled versions
following Grambsch and Therneau (1994).plot(): diagnostic plots including residuals versus
fitted values and normal Q-Q plots. For family="prophaz",
Schoenfeld residual plots are produced to assess the proportional
hazards assumption.vcov(): extracts the variance-covariance matrix of
parameter estimates for one or more estimation methods.included_realizations(): returns the indices of
realizations included in FMA and BMA model averaging.Rhat(): returns the Gelman-Rubin convergence
diagnostics and effective sample sizes for BMA results.summary_table(): extracts the summary table from a
summary.amerasfit object as a data frame, for programmatic
access to parameter estimates, standard errors, and confidence
intervals.replicate with
realization, including in names of arguments and output. As
a result, the argument included.replicates.BMA is now
deprecated and will be removed in version 1.0.0. Use
included.realizations.BMA instead.ecdfplot() now has an argument show.mean
(default TRUE) to toggle whether to plot curves for the
distribution of the mean doses across realizations and individuals.Shortened column names CI.lowerbound and
CI.upperbound in the summary() output to
CI.lower and CI.upper, respectively.
Substantially increased ERC computation speed for the
clogit and prophaz families.
Confidence intervals are no longer computed inside
ameras(). The arguments CI,
params.profCI, maxit.profCI, and
tol.profCI are deprecated and will be removed in version
1.0.0. Use the new confint() method instead. See
?confint.amerasfit for details.
The direct argument interface to ameras() is
deprecated and will be removed in version 1.0.0. The arguments
Y, dosevars, doseRRmod,
deg, M, X, offset,
entry, exit, and setnr are
deprecated. Please use the new formula interface instead. See
?ameras for details.
Implemented a formula interface for ameras(). The
dose variable is specified using the special dose() term,
which supports tidyselect syntax for selecting dose columns and allows
specifying the dose-response model and effect modifiers directly in the
formula. See ?ameras for details and examples.
Added confint.amerasfit() for computing confidence
intervals separately from model fitting. See
?confint.amerasfit for details.
Added function ecdfplot() for exploratory
visualization of the dose realizations before model fitting.
Reduced memory usage for large datasets.
summary.amerasfit() now only includes confidence
interval columns after they have been computed via
confint(). Before calling confint(), a note is
printed directing the user to compute confidence intervals.
Profile likelihood confidence interval bounds now include p-values in the summary table, making it easier to assess the accuracy of the root-finding algorithm.
Removed memoization of the profile likelihood function as it was causing issues and likely not providing much benefit.
keep.data added to ameras() (default
TRUE). When TRUE, the data are stored on the
returned amerasfit object, which is required for profile
likelihood confidence interval computation via confint()
without re-supplying the data. Set to FALSE to reduce
memory usage for large datasets, in which case the data must be supplied
to confint() explicitly. See ?ameras and
?confint.amerasfit for details.