Changes in Version 2.9.3 July 2016

 o New model added : Joint Nested frailty model for recurrent (with two clustering levels) and terminal events, accounts for two frailty terms.
 
 o For all the plot methods of frailtypack : addition of 'Xlab' and 'Ylab' (labels for the X-axis and Y-axis)
 
 o Warning added if left truncation with joint frailty model
 
 o Warning added for the use of interval-censored data in joint frailty model, the option is not available for the model
 
 o New option "initialize = TRUE" for fitting a joint frailty model to provide new initial values, before fitting the joint nested model. 
 
 o Bug fixed in models prediction with formulas defined separately

 o Bug fixed for trivPenal and longiPenal for definition of individuals identificators
 
 o Bug fixed for global Wald test for qualitative covariates in the nested and the joint frailty model

Changes in version 2.8.3 January 2016

 o Bug fixed for predictions for frailty models

 o Bug fixed for calculation of residuals for longitudinal biomarker in bivariate and trivariate models


Changes in version 2.8.2 December 2015

 o Description of the different models and options in Frailtypack using a vignette ("Package_summary")


Changes in version 2.8 November 2015

 o New models added: joint model for longitudinal data and a terminal event (longiPenal function) and trivariate joint model for longitudinal data, recurrent events and a terminal event (trivPenal function)

 o For these models summary, print and plot methods are available as well as functions epoce, Diffepoce and predictions were adapted 

 o Functions form altered: all the character options start with a capital letter, eg. was: plot(x, type.plot = "hazard") is now plot(x, type.plot = "Hazard")
 
 o Joint frailty models for clustered data now are modelled in a framework of semi-competing risks (the parameter alpha is not recommended in these semi-competing models)
 
 o Interactions are now available for all the models (using "*" or ":")


Changes in version 2.7.6 August 2015

 o New model added: Joint General frailty model for recurrent and terminal events with 2 covariates


Changes in Version 2.7.5 March  2015

 o Bug fixed for Martingale residuals (in shared and joint models with log normal frailties)


Changes in Version 2.7.3 February 2015

 o Prediction and Monte Carlo confidence bands added for shared and joint gaussian frailty models.

 o Bug fixed for the prediction function with shared or Cox models (reading of survival times)

 o Bug fixed for plotting the baseline hazard and survival functions in Weibull shared and joint models

o  New functions to compute estimators of Expected Prognostic Observed Cross-Entropy (EPOCE) evaluating prediction accuracy in joint gaussian frailty models.


Changes in Version 2.7.1 October 2014

 o Bug fixed for the multivariate Wald test for covariates with more than 3 categories.

 o Bug fixed for EPOCE, definition of kappa.


Changes in Version 2.7     August 2014

  o In 'frailPenal' and 'additivePenal' functions, no more 'kappa1', 'kappa2', 'nb.int1' and 'nb.int2'. Replaced by two vectors 'kappa' and 'nb.int'.

  o More levels of stratification (up to 6) for shared frailty model.

  o Now possible stratification in a joint frailty model for the recurrent event part (up to 6 levels).

  o New construction of the dataframe when using 'prediction' function on a joint frailty model. Need now the event indicator variable.


Changes in Version 2.6.1     July 2014

  o Different way to do Monte-Carlo method to compute confidence intervals in 'prediction' function giving less variability.

  o Back to knots placed using equidistant by default for estimating baseline hazard function with splines. You can now use the option 'hazard="Splines-per"' in frailtyPenal in order to have knots placed using percentiles.

  o Back to value 10-3 by default for the three convergence criteria.

  o No longer need to use as.factor() in command to print Wald tests on covariates.

  o Print p-value of one-sided Wald test for frailty parameter and two-sided Wald test for alpha parameter in joint model.

  o New functions to compute estimators of Expected Prognostic Observed Cross-Entropy (EPOCE) evaluating prediction accuracy in joint model.


Changes in Version 2.6       Mar 2014

  o NEW: Fit now a multivariate gaussian frailty model (two types of recurrent events and a terminal event).

  o Major evolution of frailtyPenal function. 'Frailty' and 'joint' arguments removed.

  o Now estimation of baseline hazard functions with splines, knots are placed using percentile (previously using equidistant intervals).

  o Significant change of prediction function. You can compute predictions in two different ways: with a variable prediction time or a variable window of prediction.

  o 'type' argument of prediction function removed. As long as there is a 'group' argument, for a shared model, computation of conditional predictions will be done.

  o 'B' argument added in 2.4.1 to initialize regression coefficients was renamed 'init.B'

  o Possibility to initialize the variance of the frailties with argument 'init.Theta' in shared and joint frailty models.

  o Possibility to initialize the coefficient with argument 'init.Alpha' in joint frailty model.

  o Moreover, with 'Alpha="none"', frailtyPenal can fit a joint model with a fixed alpha (=1).

  o New argument: 'print.times', added in every model to print iteration process.


Changes in Version 2.5.1       Feb 2014

  o Bug fixed about joint frailty model without any covariate.


Changes in Version 2.5         Nov 2013

  o New dynamic tool of prediction added for Cox proportionnal hazard, shared and joint frailty model.

  o Add IPCW estimation of concordance measures as Uno (Stat Med 2011). Significant changes in the printing of 'Cmeasures' function.

  o Bug fixed about parametrical survival functions plotting with left truncated data.

  o Bug fixed which allowed cross validation with interval-censored data.

  o Possibility to print and change the three convergence criterions in frailtyPenal and additivePenal.


Changes in Version 2.4.1         Apr 2013

  o Bug fixed about estimation of frailties in shared models using recurrentAG=TRUE.

  o Printing bug about standard deviation of the random effet variance in a model without covariate.

  o Possibility to initialize regression coefficients in shared and joint frailty models.


Changes in Version 2.4           Apr 2013

  o Fit now a model with time-varying effects for covariates (only for Cox, shared gamma and a joint gamma frailty model).


Changes in Version 2.3           Feb 2013

  o Fit now a Shared and a Joint Frailty model with a log-normal distribution for the random effects.

  o "Breast cosmesis" dataset added for interval-censoring illustration ("Diabetes" dataset removed).

  o Weibull hazard parameters bug fixed : shape and scale were reversed.

  o Linear predictors : output reorganized.

  o Plot options improved (now color is allowed).

  o Use of 'SurvIC' function modified. Now for the left-truncated and interval-censored data we use : SurvIC(left-trunc-time,lower-time,upper-time,event).

  o No need of the intcens argument to fit a model for interval-censored data anymore, 'SurvIC' function is enough.


Changes in Version 2.2-27        Nov 2012

  o Fit now a Joint Frailty model for clustered data.


Changes in Version 2.2-26        Oct 2012

  o Minor bug fixed about loglikelihood in Nested Frailty model.

  o The package accepts samples unsorted on clusters.


Changes in Version 2.2-25        Sep 2012

  o "Diabetes" dataset added for interval-censoring illustration.


Changes in Version 2.2-24        Jul 2012

  o Fit a Shared Gamma Frailty or a Cox proportional hazard model for interval-censored data.

  o No longer need to use cluster function for fitting a Cox proportional hazard model.

  o Minor bug fixed in Nested Frailty model.

  o Printing bug fixed in multivariate Wald test.


Changes in Version 2.2-22        Mar 2012

  o Fit a Shared Gamma Frailty model using a parametric estimation.

  o Fit Joint Frailty model for recurrent and terminal events using a parametric estimation.

  o Fit a Nested Frailty model using a parametric estimation.

  o Fit an Additive Frailty model using a parametric estimation.

  o Concordance measures in shared frailty and Cox models (Cmeasures).


Changes in Version 2.2-10

  o NEW VERSION OF FRAILTYPACK including Additive, Nested and Joint Frailty models
  o Paper submitted to Journal of Stat Software