v0.4.5

Housekeeping

• Updated Makevars and Makevars.win to remove clang4 dependency.
• Updated URL in DESCRIPTION.
• Fixed couple of typos.
• Moved to GitHub Actions CI.
• Updated URLs.

v0.4.4

New features

• Added broom compatability.

Bug patches

• Fixed issue that required subject IDs to be first column in dataset.

Housekeeping

• Added @ellessenne as package author.
• Updates to DESCRIPTION.
• Documentation updates.

v0.4.3

Housekeeping

• 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

v0.4.1

New features

• Added smoothed predicted survival curves to the plot.dynSuv(). Smoothing is based on the contrainsed 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.

Housekeeping

• Minor corrections to documentation.

• Minor bug fixes to plotting functions.

• Added MRC to DESCRIPTION as funder.

v0.4.0

New features

• 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.

Bug patches

• 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)

Housekeeping

• 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).

Canada Workshop 2017

New features

• Added new functions dynSurv() and dynLong(), which generates survival probabilities and xpected longitudinal predictions, respectively, for a new subject conditional on their last measurement time and longitudial 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 uncetered 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.

Bug patches

• 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).

Housekeeping

• 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.

v0.2.2

• This update is an attempt to overcome a FAIL status on the CRAN checks for macOS.

Housekeeping

• 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.

v0.2.1

Bug patches

• Fixed a bug that prevented factors with >2 levels being included in the time-to-event submodel.

• Fixed package registration, which strangely broke on R 3.4.0 for OSX platform.

Housekeeping

• 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.

v0.2.0

New features

• 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 outcoems 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.

Bug patches

• 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.

Housekeeping

• 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.

v0.1.1

Patches v0.1.0 to allow it to build on R versions <3.3.0