Last updated on 2026-05-22 12:49:14 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-gcc | 0.1-0 | 11.85 | 99.58 | 111.43 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.1-0 | 30.00 | 216.35 | 246.35 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 0.1-0 | 29.00 | 207.00 | 236.00 | OK | |
| r-devel-windows-x86_64 | 0.1-0 | 20.00 | 135.00 | 155.00 | ERROR | |
| r-patched-linux-x86_64 | 0.1-0 | 14.29 | 128.54 | 142.83 | OK | |
| r-release-macos-arm64 | 0.1-0 | OK | ||||
| r-release-macos-x86_64 | 0.1-0 | 12.00 | 137.00 | 149.00 | OK | |
| r-release-windows-x86_64 | 0.1-0 | 18.00 | 132.00 | 150.00 | ERROR | |
| r-oldrel-macos-arm64 | 0.1-0 | 4.00 | 37.00 | 41.00 | OK | |
| r-oldrel-macos-x86_64 | 0.1-0 | 12.00 | 110.00 | 122.00 | OK | |
| r-oldrel-windows-x86_64 | 0.1-0 | 25.00 | 171.00 | 196.00 | ERROR |
Version: 0.1-0
Check: examples
Result: ERROR
Running examples in 'mvnma-Ex.R' failed
The error most likely occurred in:
> ### Name: mvnma
> ### Title: Perform a Bayesian multivariate network meta-analysis using a
> ### single-correlation coefficient model
> ### Aliases: mvnma print.mvnma
>
> ### ** Examples
>
> # Use 'pairwise' to obtain contrast based data for the first two outcomes
>
> # Early response
> pw1 <- pairwise(treat = list(treatment1, treatment2, treatment3),
+ event = list(resp1, resp2, resp3), n = list(n1, n2, n3),
+ studlab = id, data = Linde2015, sm = "OR")
>
> # Early remissions
> pw2 <- pairwise(treat = list(treatment1, treatment2, treatment3),
+ event = list(remi1, remi2, remi3), n = list(n1, n2, n3),
+ studlab = id, data = Linde2015, sm = "OR")
>
> # Define outcome labels
> outcomes <- c("Early_Response", "Early_Remission",
+ "Adverse_events", "Loss_to_follow_up", "Loss_to_follow_up_AE")
>
> # Fit the model combining only the two efficacy outcomes
> # (note, we are using only 10 iterations and 2 burnins to reduce the
> # runtime of the example; in real applications use larger numbers)
> set.seed(1910)
> mvnma(pw1, pw2,
+ reference.group = "Placebo", outclab = outcomes[1:2],
+ n.iter = 10, n.burnin = 2)
module glm loaded
module dic loaded
Compiling model graph
Resolving undeclared variables
Allocating nodes
Graph information:
Observed stochastic nodes: 66
Unobserved stochastic nodes: 19
Total graph size: 1155
Initializing model
Outcome: Early_Response
mean 95%-CI Rhat n.eff
d[Hypericum] 0.7019 [ 0.5317; 0.8836] 1.0051 32
d[Low-dose SARI] 0.4968 [ 0.1448; 0.8842] 1.7056 7
d[NRI] 0.3336 [-0.0320; 0.6822] 1.3557 10
d[NaSSa] 0.0286 [-0.2603; 0.4717] 1.2386 12
d[SNRI] 0.6075 [ 0.3228; 0.7622] 1.0971 32
d[SSRI] 0.5036 [ 0.3406; 0.6187] 1.3800 9
d[TCA] 0.4853 [ 0.3401; 0.6146] 1.9755 6
d[rMAO-A] 0.2290 [-0.0745; 0.5619] 1.8812 6
Outcome: Early_Remission
mean 95%-CI Rhat n.eff
d[Hypericum] 0.6666 [ 0.4430; 0.9303] 1.0896 32
d[Low-dose SARI] 0.5718 [ 0.1695; 1.2443] 1.2365 13
d[NRI] 0.4750 [ 0.1616; 0.9478] 1.3958 10
d[NaSSa] 0.2851 [-0.0327; 0.7263] 1.1326 22
d[SNRI] 0.6516 [ 0.4192; 0.8417] 1.4666 9
d[SSRI] 0.5048 [ 0.3638; 0.6776] 2.3360 5
d[TCA] 0.5186 [ 0.3231; 0.6786] 3.0170 5
d[rMAO-A] 0.3046 [ 0.0229; 0.6260] 1.6204 7
>
>
>
>
>
> cleanEx()
Error: connections left open:
model.code (textConnection)
Execution halted
Flavors: r-devel-windows-x86_64, r-release-windows-x86_64, r-oldrel-windows-x86_64