Package SUGGESTS are now conditional in the vignettes per CRAN requirement.
mjoint() now returns the input inits
and the interim calculated initial values calculated for the EM
algorithm step: inits.long and inits.surv.
Requested by James Murray.
Updated Makevars and Makevars.win due to compilation issues.
Updated Makevars and Makevars.win to remove clang4 dependency.
Updated URL in DESCRIPTION.
Fixed couple of typos.
Moved to GitHub Actions CI.
Updated URLs.
broom compatibility.Added @ellessenne as package author.
Updates to DESCRIPTION.
Documentation updates.
Graeme Hickey taken over the package as creator and maintainer.
Updates to DESCRIPTION
Updates to Makevars and Makevars.win
Updates to appveyor.yml and .travis.yml settings
Updates to .gitignore
Added Zenodo DOI badge to README.
Added ORCID IDs for authors.
Remove unused objects once finished with them to try and reduce memory overheads.
Changed maintainer to Pete Philipson.
Added smoothed predicted survival curves to the
plot.dynSuv(). Smoothing is based on the constrained
B-splines method.
dynSurv() now includes an argument to specify a
horizon time from the last known observation time.
simData() now includes an argument to choose
multivariate t-distributed random effects with varying degrees
of freedom, thus allowing for sensitivity analyses of heavier tail
distributions.
Minor corrections to documentation.
Minor bug fixes to plotting functions.
Added MRC to DESCRIPTION as funder.
Added Depsy badge to README.
The MCEM algorithm can be implemented with vanilla Monte Carlo
and quasi-Monte Carlo (using either the scrambled Sobol sequence or the
Halton sequence). This is implemented through the type
argument passed to the list of control parameters in
mjoint().
bootSE() now has option to use parallel computing
via the foreach package.
Fixed some small errors in the epileptic.qol
dataset.
Fixed situation where a tibble might be given as the dataset (#55 @ellessenne).
Catches errors in bootstrap due to “bad” data and automatically restarts the bootstrap (#57 @ellessenne)
Added hex sticker badge.
Moved the make files and raw data for qol and
renal datasets into the ~/data-raw/
directory.
Added @ellessenne as package contributor for testing and bug corrections (PRs #55 and #57).
Added new functions dynSurv() and
dynLong(), which generates survival probabilities and
expected longitudinal predictions, respectively, for a new subject
conditional on their last measurement time and longitudinal history.
Prediction can be implemented using either a first order approximation
or a Monte Carlo simulation approach.
Added an associated print() method for
dynSurv and dynLong objects.
Added an associated plot() method for
dynSurv and dynLong objects.
Added a function baseHaz() for extracting the
centered and uncentered estimates of the baseline hazard
function.
print() and summary() now report the
total computation time in addition to just the EM algorithm time. This
was deemed useful after some examples showed that the time to get
initial values was more expensive than the time for the MCEM algorithm
to converge.
Fixed a bug that prevented models being fitted with no covariates
in the survival sub-model, i.e. Surv() ~ 1.
Correction to the vignette description of mjoint()
arguments.
Removed enumintem package for Sweave vignette to
satisfy CRAN checks on macOS (release).
Updated Makevars and Markvars.win to
allow for OpenMP, which can be used by RcppArmadillo.
Minor tidy-up of in-code comments.
Minor updates and corrections to documentation.
Added unit tests for new features.
Changed the technical vignette to Rnw (with engine = Sweave) from ltx (with engine = R.rsp) in attempt to remove some CMD check warnings.
Shortened the vignette to make it compile quicker (removed execution of bootstrapping).
Lots of tweaks of minor formatting tweaks in the documentation.
Fixed a bug that prevented factors with >2 levels being included in the time-to-event sub-model.
Fixed package registration, which strangely broke on R 3.4.0 for OSX platform.
joineRML version 0.2.1 will depend on R version
>=3.3.0 to remedy issue with sigma.mjoint() S3
issue.
Added a new badge to the README.
Add residual() and fitted() functions
for mjoint objects.
Added a plot function – plot.ranef.mjoint() – for
ranef.mjoint objects.
bootSE() now uses control parameters from fitted
model and allows for individual parameter overwrite.
Added a check that any initial covariance matrix given is positive-definite.
Added a check that dimensions of any inits given
match the calculated dimensions from the model formulae.
Added a check that if multiple repeated longitudinal outcomes were given, that each subject contributes at least one measurement per outcome.
Changed the API so that postRE and
approx.se arguments are now replaced by a single
pfs argument, which stands for post fit statistics. If
TRUE, then both the approximate SEs and the BLUPs
(and SEs) are calculated and returned. This change is to facilitate
other post fit statistics, e.g. residuals.
sampleData() now allows for sampling
without replacement.
plot() and plotConvergence() now have
the option to discard burn-in phase iterations from the MCEM
algorithm.
plot() and plotConvergence() now plot
the log-likelihood trace.
vcov() now calculates the variance-covariance matrix
rather than inside mjoint() and then extracting it. It also
utilises the QR-decomposition inverse function and the Moore-Penrose
matrix inverse, as in some cases the matrix was nearly
singular.
hessian() (and therefore vcov()) now
calculate the contribution for the random effect variance terms rather
than the random effect precision (1 divided by the variance) terms. The
correct contribution to the score for off-diagonal terms is now also
impleted.
The left-hand side of the formLongFixed now handles
transformations.
vcov() now returns the variance-covariance matrix as
intended. Previously it was only returning the profile empirical
information matrix.
Patched a major bug in gammaUpdate() where ties in
failure times were not being properly handled. The code for
gammaUpdate_approx() always worked fine, as it was based
only on the score vector. This bug manifested when bootSE()
was called due to the resampling with replacement yielding datasets with
many more ties than in the original dataset used to fit the model. To
fix it, the information matrix required scaling at each failure time by
the number of failures in the data. The formula for the information
matrix in the Technical Details vignette has also been updated.
Patched a minor bug with prevented univariate random-intercept models for being fitted.
Patched a minor bug in plotting convergence traces.
Patched a minor bug with bootstrapping univariate joint models
without passing the MLEs as the initial values to the
mjoint() call.
Renamed approxSE() function to
hessian().
Renamed control argument earlyPhase to
burnin.
Default settings for control parameters updated
based on practical experience.
Package now Depends on survival and
nlme rather than Imports to allow
require() statements to be removed from code.
Prevented roxygen from exporting all
functions.
Fixed Imports following CRAN Checks of v0.1.1.
Minor documentation edits and corrections.
Minor code tidy-up with slight speed-ups and stabilisations where found.
LICENSE upgraded to GPL-3 to be compatible with
joineR v1.1.0.
Removed internal function fast_nearPD() from package
code as was unused.
Removed internal function EexpArma() from package
code as was unused.
Added unit tests.
Registered native C++ routines and disabled symbol search to satisfy CRAN CMD checks.