Fit flexible (excess) hazard regression models with the possibility of including non-proportional effects of covariables and of adding a random effect at the cluster level (corresponding to a shared frailty).

Changes in Version 1.5

Fixed a bug in the mexhaz() function that resulted in an error of the function when the covariance matrix could not be estimated. Now, the function runs until completion and produces a covariance matrix filled with NA values in case it could not be estimated.

Added methods fixef() and vcov() for objects of class 'mexhaz'.

Update of the summary() method for objects of class 'mexhaz' and addition of a print() methods for objects of class 'summary.mexhaz'.

Changes in Version 1.4

Correction of a mistake in the predict.mexhaz() function that resulted in providing the limits of the confidence intervals for survival when delta.type.s="log" (CI for survival based on a Wald-type CI for the cumulative hazard) in the wrong order.

Change in the parametrisation of the Weibull hazard (the coefficients now correspond to the logarithm of the parameters of the Weibull distribution, thus allowing unconstrained optimisation).

Change in the parametrisation of the coefficient related to the random effect (the coefficient now corresponds to the logarithm of the standard deviation of the distribution of the random effect, allowing unconstrained optimisation and consistent with future multidimensional implementations).

Changes in Version 1.3

Correction of an off-by-one error in the C functions used to handle hazards described by the logarithm of a restricted cubic spline that may cause an R session crash.

Changes in Version 1.2

From a general point a view, the code of almost all functions has been modified in order to improve its clarity (suppression of redundant calculations and unnecessary variables, etc.) without modifying the obtained results. Besides, the following changes have been made:

o The 'mexhaz' function now accepts counting process style input for the follow-up time that allows the modelling of survival data with delayed entries.

o The 'base' argument of the 'mexhaz' function now accepts a new value ('exp.ns') that allows the modelling of the logarithm of the baseline hazard by a restricted cubic spline.

o The 'mexhaz' function now accepts a new argument named 'numHess' that allows the estimation of the Hessian by the 'hessian' function of the 'numDeriv' package.

o The 'bo.max' argument of the 'mexhaz' function has been replaced by a new argument named 'bound' that allows the specification of the boundary knots of spline functions.

o The following objects have been added to the output of the 'mexhaz' function: (i) the vector of initial values of the parameters ('init'), (ii) the shrinkage estimators with their standard errors ('mu.hat'), (iii) the variances of the shrinkage estimators ('var.mu.hat'), (iv) the covariances between each shrinkage estimator, the fixed effect parameter estimates ('vcov.fix.mu.hat') and (v) the name of the variable representing the expected hazard (for excess hazard regression models). (ii)-(iv) are only relevant when a random effect is present. (iii) and (iv) are used by the 'predict.mexhaz' function to obtain cluster-specific predictions with appropriate confidence intervals.

o The 'predMexhaz' has been replaced by a function named 'predict.mexhaz' and now accepts new arguments: (i) 'cluster' allows the estimation of cluster-specific predictions (only relevant when a random effect is present), (ii) 'include.gradient' allows the function to return the gradient of the logarithm of the hazard and the gradient of the logarithm of the cumulative hazard, (iii) 'level' designates the level of confidence to be used to calculate confidence intervals, (iv) 'delta.type.h' and 'delta.type.s' allow the user to choose the type of confidence interval to be calculated for the hazard and the survival when using the Delta Method.

o The 'predict.mexhaz' function also returns the covariance matrix used for the estimation of the variances and confidence intervals of the hazard and survival.

o A function 'update.mexhaz' applicable to objects of class 'mexhaz' has been added. It allows the user to update a mexhaz model by changing one or several arguments (not necessarily the formula) of the original model.

o A method 'ranef.mexhaz' applicable to objects of class 'mexhaz' has been added. It allows the extraction of the cluster-specific random effects with their standard errors.

o A bug that hampered model convergence for big datasets has been corrected in the 'FrailtyAdapt.c' file.

Changes in Version 1.1

Majors changes (no backward compatibility)! See help files for a full explanation of the arguments and outputs of the functions.

o The 'bound' argument of the 'mexhaz' function has been renamed 'bo.max'.

o The 'pl.nlm' argument of the 'mexhaz' function has been suppressed (it is still possible to print information from the nlm optimisation procedure by supplying the argument 'print.level' which will be directly passed to nlm).

o The output of the 'mexhaz' function has been modified to facilitate the application of S3 methods. The object returned by the 'mexhaz' function is a list of class 'mexhaz'.

o Methods plot() and summary() for an object of class 'mexhaz' have been added.

o The 'pred.mexhaz' function has been renamed 'predMexhaz' and its arguments have been modified: the 't' and 'nb.time.pts' have been replaced by a single argument 'time.pts' which requests the user to give a vector of time points at which the predictions are to be made; the 'delta' argument has been replaced by a 'conf.int' argument which allows the user to select the method for confidence limits calculation ("none", "delta", or "simul").

o A bug in the 'pred.mexhaz' (now, 'predMexhaz') function has been fixed: in the previous version, supplying a data.frame of covariables containing more than one line AND multiple time points (that is, trying to predict hazard/survival for different individuals at different time points) resulted in an abortion of the current R session. The problem has been solved by preventing such a situation to occur.

o The Delta Method is now available for models using a B-spline of degree 1 for the logarithm of the baseline hazard and for models using a piecewise constant hazard.

o The output of the 'predMexhaz' function has been modified to facilitate the application of S3 methods. The object returned by the 'predMexhaz' function is a list of class 'predMexhaz'.

o Methods print(), plot() and points() for an object of class 'predMexhaz' have been added.

o The function 'graph.mexhaz' has been suppressed (the methods plot() and points() are to be used instead).