Changes in version 1.6.0 (2026-03-28) - The package now supports modeling a single longitudinal outcome with heterogeneous within-subject variability via functionality adapted from the 'JMH' package. - Add DynPredAccjmcs() to calculate all available evaluation metrics for fitted joint models. - Remove AUCjmcs(), MAEQjmcs(), PEjmcs(), summary.AUCjmcs(), summary.MAEQjmcs(), and summary.PEjmcs(). Changes in version 1.5.3 (2025-11-08) - Fix small bug in survfitmvjmcs(). Changes in version 1.5.2 (2025-10-18) - Fix small bug in mvjmcs() to support ties in obtaining the estimator of the baseline hazards. Changes in version 1.5.1 (2025-07-23) - Fix small bugs and add the estimates and 95% confidence interval for the error variances of multivariate joint modeling. Changes in version 1.5.0 (2025-06-22) - Add a new function mvjmcs() to support multivariate joint modeling. Changes in version 1.4.2 (2024-02-29) - Fix small bugs within C functions. Changes in version 1.4.1 (2024-01-09) - Fix small bugs within jmcs(). Changes in version 1.4.0 (2023-10-10) - Add the function AUCjmcs() area under the ROC curve (AUC) to assess the prediction performance of joint models. Changes in version 1.3.0 - Correct the implementation of dynamic prediction in surviftjmcs(). - Remove plot.surviftjmcs() due to theoretical problem. - Provide two metrics of prediction accuracy of joint model by adding PEjmcs() and MAEQjmcs(). Changes in version 1.2.0 (2022-08-06) - Correct the implementation of dynamic prediction in surviftjmcs() for the competing risk and add summary() for providing parameter estimates and SE for both sub-models. Changes in version 1.1.3 (2022-06-01) - Correct syntax error on jmcs(). Changes in version 1.1.2 (2022-02-16) - Correct testthat error. Changes in version 1.1.1 (2022-02-14) - Correct testthat error. Changes in version 1.1.0 (2022-02-08) - Provide support for handling categorical variables in both sub-models. - Provide the anova() function to compare two fitted joint models. - Add the simulate argument in the survfitjmcs() function to obtain the conditional probabilities using the Gauss-Hermite quadrature rule for numerical integration. - Adjust the label position of y axis for clarity purposes when include.y = TRUE in the plot.survfitjmcs() function. Changes in version 1.0.1 (2022-01-11) - Removed unused variables in C functions. Changes in version 1.0.0 (2022-01-06) - First version of software with subsequent minor patches. No NEWS file was maintained.