diff --git a/docs/404.html b/docs/404.html index 2ed265c..d2373ed 100644 --- a/docs/404.html +++ b/docs/404.html @@ -52,7 +52,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/articles/Causal_Effects.html b/docs/articles/Causal_Effects.html index e06765f..8aef5e6 100644 --- a/docs/articles/Causal_Effects.html +++ b/docs/articles/Causal_Effects.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -135,7 +135,7 @@

Causal Effects

Dimitris Rizopoulos

-

2024-05-30

+

2024-06-21

Source: vignettes/Causal_Effects.Rmd diff --git a/docs/articles/Competing_Risks.html b/docs/articles/Competing_Risks.html index c675baa..8c0ec60 100644 --- a/docs/articles/Competing_Risks.html +++ b/docs/articles/Competing_Risks.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -135,7 +135,7 @@

Competing Risks

Dimitris Rizopoulos

-

2024-05-30

+

2024-06-21

Source: vignettes/Competing_Risks.Rmd @@ -297,7 +297,7 @@

Fit models#> iterations per chain: 25000 #> burn-in per chain: 5000 #> thinning: 5 -#> time: 6.6 min +#> time: 6.7 min

Dynamic predictions diff --git a/docs/articles/Dynamic_Predictions.html b/docs/articles/Dynamic_Predictions.html index 0883fba..982d576 100644 --- a/docs/articles/Dynamic_Predictions.html +++ b/docs/articles/Dynamic_Predictions.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1

@@ -135,7 +135,7 @@

Dynamic Predictions

Dimitris Rizopoulos

-

2024-05-30

+

2024-06-21

Source: vignettes/Dynamic_Predictions.Rmd @@ -354,67 +354,69 @@

Predictive accuracy#> Using information up to time: 5 (202 subjects still at risk) #> Accounting for censoring using model-based weights #> -#> cut-off SN SP qSN qSP -#> 1 0.03 0.01513 0.99812 0.01023 0.620511 -#> 2 0.08 0.03648 0.99812 0.02684 0.810255 -#> 3 0.09 0.03648 0.99168 0.02195 0.439547 -#> 4 0.11 0.10053 0.99168 0.07299 0.719773 -#> 5 0.12 0.11871 0.99072 0.08707 0.732218 -#> 6 0.13 0.11871 0.98428 0.08237 0.602957 -#> 7 0.14 0.11871 0.97783 0.07761 0.502421 -#> 8 0.16 0.15223 0.97506 0.10341 0.542026 -#> 9 0.18 0.17358 0.97506 0.12139 0.580191 -#> 10 0.20 0.21628 0.97506 0.15792 0.640163 -#> 11 0.21 0.23763 0.97506 0.17648 0.664152 -#> 12 0.25 0.25898 0.97506 0.19524 0.685143 -#> 13 0.27 0.28033 0.97506 0.21420 0.703664 -#> 14 0.30 0.32303 0.97506 0.25275 0.734857 -#> 15 0.31 0.34438 0.96862 0.26832 0.698115 -#> 16 0.33 0.37465 0.96486 0.29429 0.691398 -#> 17 0.36 0.41735 0.95842 0.33127 0.676934 -#> 18 0.37 0.41842 0.95230 0.32869 0.643114 -#> 19 0.40 0.43977 0.95230 0.34962 0.655860 -#> 20 0.44 0.47217 0.94919 0.38011 0.657861 -#> 21 0.46 0.49352 0.94919 0.40170 0.668897 -#> 22 0.48 0.53622 0.94919 0.44566 0.688964 -#> 23 0.52 0.53622 0.94274 0.44236 0.659822 -#> 24 0.53 0.53622 0.93630 0.43902 0.632345 -#> 25 0.55 0.53622 0.92985 0.43564 0.606395 -#> 26 0.56 0.57892 0.92985 0.48135 0.627111 -#> 27 0.58 0.60027 0.92985 0.50463 0.636672 -#> 28 0.65 0.60027 0.92341 0.50157 0.613208 -#> 29 0.66 0.62162 0.92341 0.52526 0.622642 * -#> 30 0.67 0.62430 0.91133 0.52270 0.583445 -#> 31 0.68 0.62430 0.90488 0.51968 0.563324 -#> 32 0.69 0.62467 0.89855 0.51709 0.544598 -#> 33 0.70 0.62467 0.89210 0.51400 0.526196 -#> 34 0.71 0.65738 0.86975 0.54166 0.484122 -#> 35 0.72 0.66080 0.85145 0.53703 0.444314 -#> 36 0.73 0.68215 0.84501 0.56023 0.440912 -#> 37 0.74 0.68626 0.83980 0.56292 0.432278 -#> 38 0.75 0.68828 0.82108 0.55656 0.397622 -#> 39 0.76 0.69336 0.80328 0.55438 0.369233 -#> 40 0.78 0.71471 0.78394 0.57312 0.348598 -#> 41 0.79 0.71977 0.77258 0.57439 0.334217 -#> 42 0.80 0.72025 0.76628 0.57190 0.325547 -#> 43 0.82 0.72770 0.74919 0.57360 0.305983 -#> 44 0.83 0.72997 0.73699 0.57050 0.291619 -#> 45 0.84 0.75693 0.71935 0.60082 0.282385 -#> 46 0.85 0.77905 0.70025 0.62495 0.270479 -#> 47 0.86 0.80262 0.68802 0.65628 0.267221 -#> 48 0.87 0.80680 0.66995 0.65464 0.250905 -#> 49 0.88 0.80680 0.66351 0.65155 0.244763 -#> 50 0.89 0.83361 0.63938 0.68588 0.233199 -#> 51 0.90 0.85678 0.60770 0.71356 0.215402 -#> 52 0.91 0.86059 0.55729 0.69719 0.179569 -#> 53 0.92 0.88371 0.52560 0.72999 0.166709 -#> 54 0.93 0.88684 0.42987 0.68252 0.114110 -#> 55 0.94 0.92954 0.40409 0.78434 0.114903 -#> 56 0.95 0.95219 0.32715 0.81776 0.087809 -#> 57 0.96 0.97587 0.24407 0.87503 0.063201 -#> 58 0.97 0.97829 0.15457 0.82457 0.035157 -#> 59 0.98 0.97829 0.09656 0.72589 0.018850 -#> 60 0.99 0.99989 0.01286 0.98859 0.002984 +#> cut-off SN SP +#> 1 0.00 0.00000 1.00000 +#> 2 0.03 0.01513 0.99812 +#> 3 0.08 0.03648 0.99812 +#> 4 0.09 0.03648 0.99168 +#> 5 0.11 0.10053 0.99168 +#> 6 0.12 0.11871 0.99072 +#> 7 0.13 0.11871 0.98428 +#> 8 0.14 0.11871 0.97783 +#> 9 0.16 0.15223 0.97506 +#> 10 0.18 0.17358 0.97506 +#> 11 0.20 0.21628 0.97506 +#> 12 0.21 0.23763 0.97506 +#> 13 0.25 0.25898 0.97506 +#> 14 0.27 0.28033 0.97506 +#> 15 0.30 0.32303 0.97506 +#> 16 0.31 0.34438 0.96862 +#> 17 0.33 0.37465 0.96486 +#> 18 0.36 0.41735 0.95842 +#> 19 0.37 0.41842 0.95230 +#> 20 0.40 0.43977 0.95230 +#> 21 0.44 0.47217 0.94919 +#> 22 0.46 0.49352 0.94919 +#> 23 0.48 0.53622 0.94919 +#> 24 0.52 0.53622 0.94274 +#> 25 0.53 0.53622 0.93630 +#> 26 0.55 0.53622 0.92985 +#> 27 0.56 0.57892 0.92985 +#> 28 0.58 0.60027 0.92985 +#> 29 0.65 0.60027 0.92341 +#> 30 0.66 0.62162 0.92341 * +#> 31 0.67 0.62430 0.91133 +#> 32 0.68 0.62430 0.90488 +#> 33 0.69 0.62467 0.89855 +#> 34 0.70 0.62467 0.89210 +#> 35 0.71 0.65738 0.86975 +#> 36 0.72 0.66080 0.85145 +#> 37 0.73 0.68215 0.84501 +#> 38 0.74 0.68626 0.83980 +#> 39 0.75 0.68828 0.82108 +#> 40 0.76 0.69336 0.80328 +#> 41 0.78 0.71471 0.78394 +#> 42 0.79 0.71977 0.77258 +#> 43 0.80 0.72025 0.76628 +#> 44 0.82 0.72770 0.74919 +#> 45 0.83 0.72997 0.73699 +#> 46 0.84 0.75693 0.71935 +#> 47 0.85 0.77905 0.70025 +#> 48 0.86 0.80262 0.68802 +#> 49 0.87 0.80680 0.66995 +#> 50 0.88 0.80680 0.66351 +#> 51 0.89 0.83361 0.63938 +#> 52 0.90 0.85678 0.60770 +#> 53 0.91 0.86059 0.55729 +#> 54 0.92 0.88371 0.52560 +#> 55 0.93 0.88684 0.42987 +#> 56 0.94 0.92954 0.40409 +#> 57 0.95 0.95219 0.32715 +#> 58 0.96 0.97587 0.24407 +#> 59 0.97 0.97829 0.15457 +#> 60 0.98 0.97829 0.09656 +#> 61 0.99 0.99989 0.01286 +#> 62 1.00 1.00000 0.00000

In the first line we define the event indicator as we did in the pbc2.id data.frame. The cut-point with the asterisk on the right maximizes the Youden’s @@ -428,7 +430,7 @@

Predictive accuracy#> #> Time-dependent AUC for the Joint Model jointFit #> -#> Estimated AUC: 0.8282 +#> Estimated AUC: 0.8282 (95% CI: 0.752-0.826) #> At time: 8 #> Using information up to time: 5 (202 subjects still at risk) #> Accounting for censoring using model-based weights @@ -497,7 +499,7 @@

Predictive accuracy#> #> Prediction Error for the Joint Model 'jointFit' #> -#> Estimated Integrated Brier score: 0.0834 +#> Estimated Integrated Brier score: 0.0841 #> In the time interval: [5, 8) #> For the 202 subjects at risk at time 5 #> Number of subjects with an event in [5, 8): 40 diff --git a/docs/articles/JMbayes2.html b/docs/articles/JMbayes2.html index 0d6616b..a6c5052 100644 --- a/docs/articles/JMbayes2.html +++ b/docs/articles/JMbayes2.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -135,7 +135,7 @@

Univariate and Multivariate Joint Models

Dimitris Rizopoulos

-

2024-05-30

+

2024-06-21

Source: vignettes/JMbayes2.Rmd @@ -215,7 +215,7 @@

Univariate#> iterations per chain: 3500 #> burn-in per chain: 500 #> thinning: 1 -#> time: 16 sec +#> time: 15 sec

The output of the summary() method provides some descriptive statistics of the sample at hand, followed by some fit statistics based on the marginal (random effects are integrated out @@ -244,6 +244,16 @@

Univariate
 ggdensityplot(jointFit1, "alphas")

+
+

Notes +

+ +

Multivariate diff --git a/docs/articles/Multi_State_Processes.html b/docs/articles/Multi_State_Processes.html index b5b6964..e7f5488 100644 --- a/docs/articles/Multi_State_Processes.html +++ b/docs/articles/Multi_State_Processes.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1

@@ -135,7 +135,7 @@

Multi-State Processes

Grigorios Papageorgiou

-

2024-05-30

+

2024-06-21

Source: vignettes/Multi_State_Processes.Rmd diff --git a/docs/articles/Non_Gaussian_Mixed_Models.html b/docs/articles/Non_Gaussian_Mixed_Models.html index fbed84d..6f8a0d7 100644 --- a/docs/articles/Non_Gaussian_Mixed_Models.html +++ b/docs/articles/Non_Gaussian_Mixed_Models.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -135,7 +135,7 @@

Non-Gaussian Mixed Models

Dimitris Rizopoulos

-

2024-05-30

+

2024-06-21

Source: vignettes/Non_Gaussian_Mixed_Models.Rmd @@ -734,7 +734,7 @@

Negative binomial mixed models#> iterations per chain: 3500 #> burn-in per chain: 500 #> thinning: 1 -#> time: 25 sec +#> time: 26 sec
Back to top
@@ -876,7 +876,7 @@

Beta-binomial longitudinal outcomes #> iterations per chain: 3500 #> burn-in per chain: 500 #> thinning: 1 -#> time: 49 sec +#> time: 50 sec diff --git a/docs/articles/Recurring_Events.html b/docs/articles/Recurring_Events.html index dc6e4ab..b357ae8 100644 --- a/docs/articles/Recurring_Events.html +++ b/docs/articles/Recurring_Events.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -135,7 +135,7 @@

Recurrent Events

Pedro Miranda Afonso

-

2024-05-30

+

2024-06-21

Source: vignettes/Recurring_Events.Rmd diff --git a/docs/articles/Super_Learning.html b/docs/articles/Super_Learning.html index 2d066bb..e1d8e76 100644 --- a/docs/articles/Super_Learning.html +++ b/docs/articles/Super_Learning.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -136,7 +136,7 @@

Combined Dynamic Predictions via Super

Dimitris Rizopoulos

-

2024-05-30

+

2024-06-21

Source: vignettes/Super_Learning.Rmd diff --git a/docs/articles/Time_Varying_Effects.html b/docs/articles/Time_Varying_Effects.html index 0a92312..c19e671 100644 --- a/docs/articles/Time_Varying_Effects.html +++ b/docs/articles/Time_Varying_Effects.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -135,7 +135,7 @@

Time Varying Effects

Dimitris Rizopoulos

-

2024-05-30

+

2024-06-21

Source: vignettes/Time_Varying_Effects.Rmd @@ -289,7 +289,7 @@

Non Proportional Hazards#> iterations per chain: 6500 #> burn-in per chain: 2500 #> thinning: 1 -#> time: 36 sec +#> time: 35 sec

The spline coefficients do not have a straightforward interpretation. We, therefore, visualize the time-varying association of log serum bilirubin with the hazard of the composite event using the following diff --git a/docs/articles/Transformation_Functions.html b/docs/articles/Transformation_Functions.html index 156ebaf..b5e45e7 100644 --- a/docs/articles/Transformation_Functions.html +++ b/docs/articles/Transformation_Functions.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -136,7 +136,7 @@

Transformation Functions for Functional

Dimitris Rizopoulos

-

2024-05-30

+

2024-06-21

Source: vignettes/Transformation_Functions.Rmd diff --git a/docs/articles/index.html b/docs/articles/index.html index fece374..5d74ba2 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/authors.html b/docs/authors.html index 7632f00..a1a8a7f 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -119,13 +119,13 @@

Citation

Rizopoulos D, Papageorgiou G, Miranda Afonso P (2024). JMbayes2: Extended Joint Models for Longitudinal and Time-to-Event Data. -R package version 0.5-0, https://github.com/drizopoulos/JMbayes2, https://drizopoulos.github.io/JMbayes2/. +R package version 0.5-1, https://github.com/drizopoulos/JMbayes2, https://drizopoulos.github.io/JMbayes2/. 

@Manual{,
   title = {JMbayes2: Extended Joint Models for Longitudinal and Time-to-Event Data},
   author = {Dimitris Rizopoulos and Grigorios Papageorgiou and Pedro {Miranda Afonso}},
   year = {2024},
-  note = {R package version 0.5-0, https://github.com/drizopoulos/JMbayes2},
+  note = {R package version 0.5-1, https://github.com/drizopoulos/JMbayes2},
   url = {https://drizopoulos.github.io/JMbayes2/},
 }
diff --git a/docs/index.html b/docs/index.html index 89ff4b2..f1755ef 100644 --- a/docs/index.html +++ b/docs/index.html @@ -53,7 +53,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/news/index.html b/docs/news/index.html index c558aba..fc924a0 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 0029423..a214fdc 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -12,7 +12,7 @@ articles: Super_Learning: Super_Learning.html Time_Varying_Effects: Time_Varying_Effects.html Transformation_Functions: Transformation_Functions.html -last_built: 2024-05-30T15:41Z +last_built: 2024-06-21T09:29Z urls: reference: https://drizopoulos.github.io/JMbayes2/reference article: https://drizopoulos.github.io/JMbayes2/articles diff --git a/docs/reference/JMbayes2.html b/docs/reference/JMbayes2.html index b95abe0..abc00a2 100644 --- a/docs/reference/JMbayes2.html +++ b/docs/reference/JMbayes2.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -104,7 +104,7 @@

Extended Joint Models for Longitudinal and Time-to-Event Data

Details

-
Package:JMbayes2
Type:Package
Version:0.5-0
Date:2024-05-30
License:GPL (>=3)

This package fits joint models for longitudinal and time-to-event data. It can accommodate multiple longitudinal outcomes of different type (e.g., continuous, dichotomous, ordinal, counts), and assuming different distributions, i.e., Gaussian, Student's-t, Gamma, Beta, unit Lindley, censored Normal, Binomial, Poisson, Negative Binomial, and Beta-Binomial. For the event time process, right, left and interval censored data can be handled, while competing risks and multi-sate processes are also covered.

+
Package:JMbayes2
Type:Package
Version:0.5-1
Date:2024-06-05
License:GPL (>=3)

This package fits joint models for longitudinal and time-to-event data. It can accommodate multiple longitudinal outcomes of different type (e.g., continuous, dichotomous, ordinal, counts), and assuming different distributions, i.e., Gaussian, Student's-t, Gamma, Beta, unit Lindley, censored Normal, Binomial, Poisson, Negative Binomial, and Beta-Binomial. For the event time process, right, left and interval censored data can be handled, while competing risks and multi-sate processes are also covered.

JMbayes2 fits joint models using Markov chain Monte Carlo algorithms implemented in C++. The package also offers several utility functions that can extract useful information from fitted joint models. The most important of those are included in the See also Section below.

diff --git a/docs/reference/accuracy.html b/docs/reference/accuracy.html index 31bcf57..efdbd3a 100644 --- a/docs/reference/accuracy.html +++ b/docs/reference/accuracy.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1
@@ -336,83 +336,85 @@

Examples

#> Using information up to time: 4 (225 subjects still at risk) #> Accounting for censoring using model-based weights #> -#> cut-off SN SP qSN qSP -#> 1 0.01 0.01306 0.9978 0.008649 0.497080 -#> 2 0.03 0.02703 0.9958 0.018304 0.523635 -#> 3 0.05 0.04880 0.9958 0.035944 0.682423 -#> 4 0.06 0.06077 0.9933 0.043768 0.620426 -#> 5 0.07 0.06077 0.9877 0.039421 0.445027 -#> 6 0.08 0.08253 0.9877 0.057399 0.537523 -#> 7 0.09 0.10430 0.9877 0.075541 0.603591 -#> 8 0.10 0.12607 0.9877 0.093851 0.653142 -#> 9 0.13 0.14478 0.9813 0.105000 0.579203 -#> 10 0.17 0.15942 0.9795 0.116214 0.580071 -#> 11 0.18 0.18119 0.9795 0.135058 0.615065 -#> 12 0.19 0.18119 0.9739 0.130979 0.548016 -#> 13 0.20 0.23145 0.9700 0.172618 0.578512 -#> 14 0.21 0.28848 0.9679 0.222860 0.619934 -#> 15 0.22 0.30214 0.9658 0.234054 0.615519 -#> 16 0.23 0.32391 0.9602 0.250634 0.593356 -#> 17 0.25 0.34567 0.9602 0.271170 0.611036 -#> 18 0.26 0.36360 0.9481 0.280456 0.550739 -#> 19 0.30 0.36360 0.9425 0.276822 0.520839 -#> 20 0.32 0.38537 0.9425 0.298012 0.537952 -#> 21 0.34 0.40714 0.9425 0.319419 0.553885 -#> 22 0.36 0.42891 0.9369 0.337648 0.542132 -#> 23 0.37 0.45067 0.9369 0.359592 0.556440 -#> 24 0.41 0.49421 0.9369 0.404170 0.582532 -#> 25 0.45 0.50564 0.9287 0.411472 0.554243 -#> 26 0.46 0.50564 0.9231 0.408341 0.532330 -#> 27 0.47 0.51426 0.9141 0.412414 0.504642 -#> 28 0.51 0.52846 0.9066 0.423386 0.487496 -#> 29 0.54 0.53187 0.8963 0.421267 0.457469 -#> 30 0.55 0.55364 0.8851 0.438929 0.438218 -#> 31 0.56 0.56056 0.8813 0.444526 0.431937 -#> 32 0.57 0.60409 0.8758 0.490976 0.440889 -#> 33 0.58 0.64763 0.8758 0.541711 0.462393 -#> 34 0.60 0.66939 0.8758 0.567521 0.472537 -#> 35 0.61 0.66939 0.8702 0.564992 0.459035 -#> 36 0.62 0.66939 0.8590 0.559844 0.433478 -#> 37 0.63 0.69619 0.8547 0.590678 0.436355 -#> 38 0.65 0.71796 0.8547 0.617716 0.445908 -#> 39 0.66 0.71796 0.8491 0.615399 0.434201 -#> 40 0.68 0.71908 0.8382 0.612232 0.412965 -#> 41 0.69 0.74085 0.8382 0.640071 0.422283 * -#> 42 0.70 0.74085 0.8327 0.637835 0.411676 -#> 43 0.71 0.74530 0.8282 0.641835 0.405351 -#> 44 0.72 0.74530 0.8226 0.639582 0.395322 -#> 45 0.73 0.74530 0.8059 0.632651 0.366979 -#> 46 0.74 0.76707 0.8059 0.661879 0.376022 -#> 47 0.75 0.77172 0.7847 0.659845 0.345452 -#> 48 0.76 0.77172 0.7791 0.657577 0.337425 -#> 49 0.77 0.77398 0.7630 0.654051 0.316253 -#> 50 0.78 0.77398 0.7574 0.651681 0.309002 -#> 51 0.79 0.77398 0.7462 0.646844 0.295038 -#> 52 0.80 0.79806 0.7412 0.680033 0.298498 -#> 53 0.81 0.82369 0.7255 0.712546 0.289984 -#> 54 0.82 0.83206 0.6997 0.715898 0.265531 -#> 55 0.83 0.85792 0.6784 0.750250 0.254007 -#> 56 0.84 0.85843 0.6618 0.745171 0.238983 -#> 57 0.85 0.86268 0.6349 0.742523 0.217722 -#> 58 0.86 0.86854 0.5918 0.735898 0.187136 -#> 59 0.87 0.87327 0.5762 0.738404 0.178018 -#> 60 0.88 0.87327 0.5483 0.725827 0.160060 -#> 61 0.89 0.87385 0.5373 0.721718 0.153555 -#> 62 0.90 0.88081 0.4609 0.695258 0.114580 -#> 63 0.91 0.90438 0.4390 0.740801 0.111094 -#> 64 0.92 0.92843 0.4228 0.796159 0.110529 -#> 65 0.93 0.92945 0.3784 0.776413 0.091840 -#> 66 0.94 0.93024 0.3339 0.750849 0.074917 -#> 67 0.95 0.99618 0.2783 0.982831 0.072046 -#> 68 0.96 0.99936 0.1897 0.995734 0.045477 -#> 69 0.97 0.99963 0.1172 0.996022 0.026306 -#> 70 0.98 0.99990 0.0279 0.995653 0.005806 +#> cut-off SN SP +#> 1 0.00 0.00000 1.0000 +#> 2 0.01 0.01306 0.9978 +#> 3 0.03 0.02703 0.9958 +#> 4 0.05 0.04880 0.9958 +#> 5 0.06 0.06077 0.9933 +#> 6 0.07 0.06077 0.9877 +#> 7 0.08 0.08253 0.9877 +#> 8 0.09 0.10430 0.9877 +#> 9 0.10 0.12607 0.9877 +#> 10 0.13 0.14478 0.9813 +#> 11 0.17 0.15942 0.9795 +#> 12 0.18 0.18119 0.9795 +#> 13 0.19 0.18119 0.9739 +#> 14 0.20 0.23145 0.9700 +#> 15 0.21 0.28848 0.9679 +#> 16 0.22 0.30214 0.9658 +#> 17 0.23 0.32391 0.9602 +#> 18 0.25 0.34567 0.9602 +#> 19 0.26 0.36360 0.9481 +#> 20 0.30 0.36360 0.9425 +#> 21 0.32 0.38537 0.9425 +#> 22 0.34 0.40714 0.9425 +#> 23 0.36 0.42891 0.9369 +#> 24 0.37 0.45067 0.9369 +#> 25 0.41 0.49421 0.9369 +#> 26 0.45 0.50564 0.9287 +#> 27 0.46 0.50564 0.9231 +#> 28 0.47 0.51426 0.9141 +#> 29 0.51 0.52846 0.9066 +#> 30 0.54 0.53187 0.8963 +#> 31 0.55 0.55364 0.8851 +#> 32 0.56 0.56056 0.8813 +#> 33 0.57 0.60409 0.8758 +#> 34 0.58 0.64763 0.8758 +#> 35 0.60 0.66939 0.8758 +#> 36 0.61 0.66939 0.8702 +#> 37 0.62 0.66939 0.8590 +#> 38 0.63 0.69619 0.8547 +#> 39 0.65 0.71796 0.8547 +#> 40 0.66 0.71796 0.8491 +#> 41 0.68 0.71908 0.8382 +#> 42 0.69 0.74085 0.8382 * +#> 43 0.70 0.74085 0.8327 +#> 44 0.71 0.74530 0.8282 +#> 45 0.72 0.74530 0.8226 +#> 46 0.73 0.74530 0.8059 +#> 47 0.74 0.76707 0.8059 +#> 48 0.75 0.77172 0.7847 +#> 49 0.76 0.77172 0.7791 +#> 50 0.77 0.77398 0.7630 +#> 51 0.78 0.77398 0.7574 +#> 52 0.79 0.77398 0.7462 +#> 53 0.80 0.79806 0.7412 +#> 54 0.81 0.82369 0.7255 +#> 55 0.82 0.83206 0.6997 +#> 56 0.83 0.85792 0.6784 +#> 57 0.84 0.85843 0.6618 +#> 58 0.85 0.86268 0.6349 +#> 59 0.86 0.86854 0.5918 +#> 60 0.87 0.87327 0.5762 +#> 61 0.88 0.87327 0.5483 +#> 62 0.89 0.87385 0.5373 +#> 63 0.90 0.88081 0.4609 +#> 64 0.91 0.90438 0.4390 +#> 65 0.92 0.92843 0.4228 +#> 66 0.93 0.92945 0.3784 +#> 67 0.94 0.93024 0.3339 +#> 68 0.95 0.99618 0.2783 +#> 69 0.96 0.99936 0.1897 +#> 70 0.97 0.99963 0.1172 +#> 71 0.98 0.99990 0.0279 +#> 72 0.99 1.00000 0.0000 #> tvAUC(roc) #> #> Time-dependent AUC for the Joint Model jointFit #> -#> Estimated AUC: 0.8374 +#> Estimated AUC: 0.8374 (95% CI: 0.7618-0.8338) #> At time: 7 #> Using information up to time: 4 (225 subjects still at risk) #> Accounting for censoring using model-based weights diff --git a/docs/reference/aids.html b/docs/reference/aids.html index 10f4683..28498ac 100644 --- a/docs/reference/aids.html +++ b/docs/reference/aids.html @@ -24,7 +24,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/reference/coda_methods.html b/docs/reference/coda_methods.html index 8e4ad07..8906558 100644 --- a/docs/reference/coda_methods.html +++ b/docs/reference/coda_methods.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/reference/cr_setup.html b/docs/reference/cr_setup.html index 71c45df..584fec5 100644 --- a/docs/reference/cr_setup.html +++ b/docs/reference/cr_setup.html @@ -25,7 +25,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/reference/index.html b/docs/reference/index.html index 71736b7..693acb1 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/reference/jm.html b/docs/reference/jm.html index 34f03b6..828625f 100644 --- a/docs/reference/jm.html +++ b/docs/reference/jm.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 @@ -389,7 +389,9 @@

Arguments

Details

The mathematical details regarding the definition of the multivariate joint model, and the capabilities of the package can be found in the vignette in the doc directory.

-
+

Notes:

Value

@@ -509,7 +511,7 @@

Examples

#> iterations per chain: 11000 #> burn-in per chain: 1000 #> thinning: 1 -#> time: 37 sec +#> time: 36 sec traceplot(joint_model_fit_1) @@ -789,7 +791,7 @@

Examples

#> iterations per chain: 11000 #> burn-in per chain: 1000 #> thinning: 1 -#> time: 1.6 min +#> time: 1.8 min # }
diff --git a/docs/reference/methods.html b/docs/reference/methods.html index dbdcfff..00d452d 100644 --- a/docs/reference/methods.html +++ b/docs/reference/methods.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/reference/pbc.html b/docs/reference/pbc.html index bf6d060..1cfac78 100644 --- a/docs/reference/pbc.html +++ b/docs/reference/pbc.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/reference/predict.html b/docs/reference/predict.html index 3a286e5..184d353 100644 --- a/docs/reference/predict.html +++ b/docs/reference/predict.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/reference/prothro.html b/docs/reference/prothro.html index 8d94e79..be06f1f 100644 --- a/docs/reference/prothro.html +++ b/docs/reference/prothro.html @@ -23,7 +23,7 @@ JMbayes2 - 0.5-0 + 0.5-1 diff --git a/docs/reference/rc_setup.html b/docs/reference/rc_setup.html index 3f7a591..3fcd3fe 100644 --- a/docs/reference/rc_setup.html +++ b/docs/reference/rc_setup.html @@ -25,7 +25,7 @@ JMbayes2 - 0.5-0 + 0.5-1