Changes in Version 3.0.3.2 may 2019
o Correction of warnings during installation of package
o Bug fixed for printing results of longiPenal, trivPenal and trivPenalNL
o Add of the median survival
o Bug fixed when characters are used in data for prediction
o Rename gammaJ as logGammaJ
o Error message for a bad use of jointGeneral

Changes in Version 3.0.3.1 march 2019
o Bug fixed in subroutines Fortran for the computation of integrals using the Pseudo-adaptive Gaussian Hermite quadrature. Due to incorrect assignment of memory (variable V_i and V in the subroutines funcpajsplines_surrogate, funcpafrailtyPred_Essai and MC_Gauss_MultInd_Essai), the program encountered in the previous version a fatal error with Windows OS. However, this problem did not impact model estimates based on other OS. 

o Add of the R function loocv() for the leave-one-out crossvalidation to evaluate the joint surrogate model

o Add of the function to use to predict the treatment effect on the true endpoint basing on the treatment effect observed on te surrogate endpoint

o Add of the function to use to compute the surrogate threshold effect (STE)

o Upadate of the values of the function jointSurroPenal() and jointSurroPenalSimul(). Several other values are returned to these function.

o Update of the subroutine Fortran jointsurrogate(). Computation of the variance-covariance matrix for the estimates of the variance-covariance parameters of the random effect treatment-by-trial interaction using the delta-method. we also return in this function the dataframes for the estimates and their variance-covariance matrices. 

o Update of the output of the R function summary.jointSurroPenal(). Categorization of the Correlation strength at trial level. We also compute and display the STE in this function.

o Parameters "indice.zeta and "indice.alpha" in the R functions jointSurroPenal and jointSurrPenalSimul are renamed by "indicator.zeta" and "indicator.alpha"

Changes in Version 3.0.2 December 2018
o Bug fixed in the file aaOptim_New_scl.o, aaOptim_New_scl2.o and aaOptim_SCL_0.o: module type definition remove, already defined in the file aaOptim.o 

o Bug fixed in function jointSurroPenal: an error occurs in case of convergence issue. it is corrected  now

o Argument color remove in the function plot.jointSurroPenal

Changes in Version 3.0.1 November 2018

o New model added: Joint frailty models for the validation of surrogate endpoints in multiple randomized clinical trials with failure-time endpoints (vignettes file updated)

o Parsing all the Rd files under the man directory and updating the corresponding R source code by inserting roxygen documentation into the R scripts

o Bug fixed in summary function for jointNestedPenal when alpha or ksi is not included in the model and JointPenal when alpha is not included in the model
 
o Bug fixed for predictions from joint nested frailty models with data with different values of covariates for a given individuals
 
o Bug fixed for confidence intervals of predictions from joint nested frailty models without one or two power parameters (alpha, ksi) included in the model
 
o Bug fixed for displaying for baseline hazard function (lam) for Piecewise hazard functions in frailtyPenal

o Bug fixed for trivPenalNL: missing parenthesis was leading to an error when adjusting on covariates in KG part

o Modification in longiPenal: Switch optimizer from nlminb to optim (BFGS) to get the initial values for pseudo-adaptive quadrature (better convergence rates)

o Modification of the writing of the p-value

o Bug fixed in the Fortran subroutines percentile, percentile2 and percentile3: change in the subroutine to account for vector overflows + update of the percentile formula

Changes in Version 2.13.2 September 2018

 o Bug fixed for predictions for prediction data with only one observation per individual


Changes in Version 2.13.1 September 2018

o  NEW: Weighted penalized maximum likelihood approach for joint frailty models for data from nested case-control studies

o  Bug corrected in predictions with joint nested frailty models that do not include power parameters 


Changes in Version 2.12.7 July 2018

o  Now the p-values of the estimates can be directly extracted from the models

o  Small bugs corrected in epoce, trivPenal, trivPenalNL, prediction and print.JointNestedPenal

o Shared frailty model (Weibull baseline hazard function, calendar time-scale and log-normal frailty) now works


Changes in Version 2.12.6 October 2017

o For joint nested and nested models martingale residuals are calculated at the lower level of clustering (individual level)


Changes in Version 2.12.3 July 2017 

o Bug fixed in predictions for trivariate joint models.


Changes in Version 2.12.2 June 2017

o Bug fixed in predictions for joint nested frailty models.


Changes in Version 2.12.0 June 2017

 o New model added: trivariate joint model for a longitudinal biomarker, recurrent events and a terminal event using a mechanistic approach for the biomarker (with analytical solution)
 
 o Extension for functions longiPenal and trivPenal: up to three random effects for the biomarker can be applied
 
 o Bug fixed : Estimation error in joint, joint general, joint nested, trivPenal and longiPenal models when data are unordered.
 
 o Bug fixed for predictions using joint nested models - application of Gamma function
 
 
Changes in Version 2.11.1 March 2017

 o Warnings about native subroutine registry fixed

 
Changes in Version 2.11.0 March 2017

 o NEW : Marginal prediction method in the Joint Nested Frailty model, only for terminal event.

 
Changes in Version 2.10.6 March 2017

 o Bug fixed in the conditional prediction for shared frailty model. 
 
 o New warning for the prediction in joint general model.
 
 
Changes in Version 2.10.5 February 2017

 o Bug fixed : use of a subcluster/cluster covariate named with upper case in joint and joint nested models 
 
 o Bug fixed : Joint nested model estimation 
 
 o Bug fixed : Conditional prediction for recurrent events from a shared model.
 
 o Bug fixed : examples of the documentation (plot of epoce, additive model, trivariate and joint nested model)

 
Changes in Version 2.10.4 January 2017

 o Changes in the joint nested frailty model : add calculation of the bayesian frailties estimates (for families and for individuals)

 o Problem fixed : survival() function in frailtypack can now be computed with a gamma shared frailty model with a piecewise baseline hazard function
 
 o Changes in the prediction() function : 'group' argument removed and 'conditional' boolean argument added

 o Changes in the conditional prediction method for shared modelling : possibility to compute prediction for more than one group

 o Display of prediction's results : for each indivual you can see the true ID

 o Problem fixed : prediction() function is now able to compute with disorderly individuals

 o Changes in the prediction method : you can now use the prediction methods with time-dependant covariates 
    
 o NEW: Marginal prediction method in the shared modelling, for a recurrent event.
 
 o Correction applied on the mathematical expression of prediction method from shared model

 
Changes in Version 2.10.3 October 2016

 o "na.pass" global function defined in the NAMESPACE file
 
 o Update of the vignettes 'Package_summary.Rmd' in the 'inst/doc' directory  
 
 
Changes in Version 2.10.2 October 2016

 o Vignettes modified (legend in the title)
 
 o 'event' legend deleted in the plot of a shared model
 
 o Compiling warnings fixed
 
 o Plot bug fixed in the plot of a shared model
 

Changes in Version 2.10.1 July 2016
 
 o New prediction option for a new recurrent event.
 
 o Bug fixed for the gfortran compilation
 

Changes in Version 2.9.4 July 2016

 o Bug fixed for the vignettes builder


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       March 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       February 2014

  o Bug fixed about joint frailty model without any covariate.


Changes in Version 2.5         November 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         April 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           April 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           February 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        November 2012

  o Fit now a Joint Frailty model for clustered data.


Changes in Version 2.2-26        October 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        September 2012

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


Changes in Version 2.2-24        July 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        March 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