R Under development (unstable) (2024-06-07 r86704 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(multinma)
For execution on a local, multicore CPU with excess RAM we recommend calling
options(mc.cores = parallel::detectCores())

Attaching package: 'multinma'

The following objects are masked from 'package:stats':

    dgamma, pgamma, qgamma

> 
> test_check("multinma")

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'normal' NOW (CHAIN 4).

SAMPLING FOR MODEL 'binomial_1par' NOW (CHAIN 1).
Chain 1: 
Chain 1: Gradient evaluation took 2.1e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.21 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1: 
Chain 1: 
Chain 1: WARNING: There aren't enough warmup iterations to fit the
Chain 1:          three stages of adaptation as currently configured.
Chain 1:          Reducing each adaptation stage to 15%/75%/10% of
Chain 1:          the given number of warmup iterations:
Chain 1:            init_buffer = 7
Chain 1:            adapt_window = 38
Chain 1:            term_buffer = 5
Chain 1: 
Chain 1: Iteration:  1 / 100 [  1%]  (Warmup)
Chain 1: Iteration: 10 / 100 [ 10%]  (Warmup)
Chain 1: Iteration: 20 / 100 [ 20%]  (Warmup)
Chain 1: Iteration: 30 / 100 [ 30%]  (Warmup)
Chain 1: Iteration: 40 / 100 [ 40%]  (Warmup)
Chain 1: Iteration: 50 / 100 [ 50%]  (Warmup)
Chain 1: Iteration: 51 / 100 [ 51%]  (Sampling)
Chain 1: Iteration: 60 / 100 [ 60%]  (Sampling)
Chain 1: Iteration: 70 / 100 [ 70%]  (Sampling)
Chain 1: Iteration: 80 / 100 [ 80%]  (Sampling)
Chain 1: Iteration: 90 / 100 [ 90%]  (Sampling)
Chain 1: Iteration: 100 / 100 [100%]  (Sampling)
Chain 1: 
Chain 1:  Elapsed Time: 0.019 seconds (Warm-up)
Chain 1:                0.019 seconds (Sampling)
Chain 1:                0.038 seconds (Total)
Chain 1: 

SAMPLING FOR MODEL 'binomial_1par' NOW (CHAIN 2).
Chain 2: 
Chain 2: Gradient evaluation took 1.3e-05 seconds
Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.13 seconds.
Chain 2: Adjust your expectations accordingly!
Chain 2: 
Chain 2: 
Chain 2: WARNING: There aren't enough warmup iterations to fit the
Chain 2:          three stages of adaptation as currently configured.
Chain 2:          Reducing each adaptation stage to 15%/75%/10% of
Chain 2:          the given number of warmup iterations:
Chain 2:            init_buffer = 7
Chain 2:            adapt_window = 38
Chain 2:            term_buffer = 5
Chain 2: 
Chain 2: Iteration:  1 / 100 [  1%]  (Warmup)
Chain 2: Iteration: 10 / 100 [ 10%]  (Warmup)
Chain 2: Iteration: 20 / 100 [ 20%]  (Warmup)
Chain 2: Iteration: 30 / 100 [ 30%]  (Warmup)
Chain 2: Iteration: 40 / 100 [ 40%]  (Warmup)
Chain 2: Iteration: 50 / 100 [ 50%]  (Warmup)
Chain 2: Iteration: 51 / 100 [ 51%]  (Sampling)
Chain 2: Iteration: 60 / 100 [ 60%]  (Sampling)
Chain 2: Iteration: 70 / 100 [ 70%]  (Sampling)
Chain 2: Iteration: 80 / 100 [ 80%]  (Sampling)
Chain 2: Iteration: 90 / 100 [ 90%]  (Sampling)
Chain 2: Iteration: 100 / 100 [100%]  (Sampling)
Chain 2: 
Chain 2:  Elapsed Time: 0.025 seconds (Warm-up)
Chain 2:                0.019 seconds (Sampling)
Chain 2:                0.044 seconds (Total)
Chain 2: 

SAMPLING FOR MODEL 'binomial_1par' NOW (CHAIN 3).
Chain 3: 
Chain 3: Gradient evaluation took 1.3e-05 seconds
Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.13 seconds.
Chain 3: Adjust your expectations accordingly!
Chain 3: 
Chain 3: 
Chain 3: WARNING: There aren't enough warmup iterations to fit the
Chain 3:          three stages of adaptation as currently configured.
Chain 3:          Reducing each adaptation stage to 15%/75%/10% of
Chain 3:          the given number of warmup iterations:
Chain 3:            init_buffer = 7
Chain 3:            adapt_window = 38
Chain 3:            term_buffer = 5
Chain 3: 
Chain 3: Iteration:  1 / 100 [  1%]  (Warmup)
Chain 3: Iteration: 10 / 100 [ 10%]  (Warmup)
Chain 3: Iteration: 20 / 100 [ 20%]  (Warmup)
Chain 3: Iteration: 30 / 100 [ 30%]  (Warmup)
Chain 3: Iteration: 40 / 100 [ 40%]  (Warmup)
Chain 3: Iteration: 50 / 100 [ 50%]  (Warmup)
Chain 3: Iteration: 51 / 100 [ 51%]  (Sampling)
Chain 3: Iteration: 60 / 100 [ 60%]  (Sampling)
Chain 3: Iteration: 70 / 100 [ 70%]  (Sampling)
Chain 3: Iteration: 80 / 100 [ 80%]  (Sampling)
Chain 3: Iteration: 90 / 100 [ 90%]  (Sampling)
Chain 3: Iteration: 100 / 100 [100%]  (Sampling)
Chain 3: 
Chain 3:  Elapsed Time: 0.021 seconds (Warm-up)
Chain 3:                0.02 seconds (Sampling)
Chain 3:                0.041 seconds (Total)
Chain 3: 

SAMPLING FOR MODEL 'binomial_1par' NOW (CHAIN 4).
Chain 4: 
Chain 4: Gradient evaluation took 1.3e-05 seconds
Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0.13 seconds.
Chain 4: Adjust your expectations accordingly!
Chain 4: 
Chain 4: 
Chain 4: WARNING: There aren't enough warmup iterations to fit the
Chain 4:          three stages of adaptation as currently configured.
Chain 4:          Reducing each adaptation stage to 15%/75%/10% of
Chain 4:          the given number of warmup iterations:
Chain 4:            init_buffer = 7
Chain 4:            adapt_window = 38
Chain 4:            term_buffer = 5
Chain 4: 
Chain 4: Iteration:  1 / 100 [  1%]  (Warmup)
Chain 4: Iteration: 10 / 100 [ 10%]  (Warmup)
Chain 4: Iteration: 20 / 100 [ 20%]  (Warmup)
Chain 4: Iteration: 30 / 100 [ 30%]  (Warmup)
Chain 4: Iteration: 40 / 100 [ 40%]  (Warmup)
Chain 4: Iteration: 50 / 100 [ 50%]  (Warmup)
Chain 4: Iteration: 51 / 100 [ 51%]  (Sampling)
Chain 4: Iteration: 60 / 100 [ 60%]  (Sampling)
Chain 4: Iteration: 70 / 100 [ 70%]  (Sampling)
Chain 4: Iteration: 80 / 100 [ 80%]  (Sampling)
Chain 4: Iteration: 90 / 100 [ 90%]  (Sampling)
Chain 4: Iteration: 100 / 100 [100%]  (Sampling)
Chain 4: 
Chain 4:  Elapsed Time: 0.018 seconds (Warm-up)
Chain 4:                0.019 seconds (Sampling)
Chain 4:                0.037 seconds (Total)
Chain 4: 

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).

SAMPLING FOR MODEL 'binomial_1par' NOW (CHAIN 1).
Chain 1: 
Chain 1: Gradient evaluation took 2.8e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.28 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1: 
Chain 1: 
Chain 1: WARNING: No variance estimation is
Chain 1:          performed for num_warmup < 20
Chain 1: 
Chain 1: Iteration: 1 / 10 [ 10%]  (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%]  (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%]  (Warmup)
Chain 1: Iteration: 4 / 10 [ 40%]  (Warmup)
Chain 1: Iteration: 5 / 10 [ 50%]  (Warmup)
Chain 1: Iteration: 6 / 10 [ 60%]  (Sampling)
Chain 1: Iteration: 7 / 10 [ 70%]  (Sampling)
Chain 1: Iteration: 8 / 10 [ 80%]  (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
Chain 1: 
Chain 1:  Elapsed Time: 0 seconds (Warm-up)
Chain 1:                0 seconds (Sampling)
Chain 1:                0 seconds (Total)
Chain 1: 

SAMPLING FOR MODEL 'binomial_1par' NOW (CHAIN 2).
Chain 2: 
Chain 2: Gradient evaluation took 2e-05 seconds
Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.2 seconds.
Chain 2: Adjust your expectations accordingly!
Chain 2: 
Chain 2: 
Chain 2: WARNING: No variance estimation is
Chain 2:          performed for num_warmup < 20
Chain 2: 
Chain 2: Iteration: 1 / 10 [ 10%]  (Warmup)
Chain 2: Iteration: 2 / 10 [ 20%]  (Warmup)
Chain 2: Iteration: 3 / 10 [ 30%]  (Warmup)
Chain 2: Iteration: 4 / 10 [ 40%]  (Warmup)
Chain 2: Iteration: 5 / 10 [ 50%]  (Warmup)
Chain 2: Iteration: 6 / 10 [ 60%]  (Sampling)
Chain 2: Iteration: 7 / 10 [ 70%]  (Sampling)
Chain 2: Iteration: 8 / 10 [ 80%]  (Sampling)
Chain 2: Iteration: 9 / 10 [ 90%]  (Sampling)
Chain 2: Iteration: 10 / 10 [100%]  (Sampling)
Chain 2: 
Chain 2:  Elapsed Time: 0 seconds (Warm-up)
Chain 2:                0.001 seconds (Sampling)
Chain 2:                0.001 seconds (Total)
Chain 2: 

SAMPLING FOR MODEL 'binomial_1par' NOW (CHAIN 3).
Chain 3: 
Chain 3: Gradient evaluation took 1.9e-05 seconds
Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.19 seconds.
Chain 3: Adjust your expectations accordingly!
Chain 3: 
Chain 3: 
Chain 3: WARNING: No variance estimation is
Chain 3:          performed for num_warmup < 20
Chain 3: 
Chain 3: Iteration: 1 / 10 [ 10%]  (Warmup)
Chain 3: Iteration: 2 / 10 [ 20%]  (Warmup)
Chain 3: Iteration: 3 / 10 [ 30%]  (Warmup)
Chain 3: Iteration: 4 / 10 [ 40%]  (Warmup)
Chain 3: Iteration: 5 / 10 [ 50%]  (Warmup)
Chain 3: Iteration: 6 / 10 [ 60%]  (Sampling)
Chain 3: Iteration: 7 / 10 [ 70%]  (Sampling)
Chain 3: Iteration: 8 / 10 [ 80%]  (Sampling)
Chain 3: Iteration: 9 / 10 [ 90%]  (Sampling)
Chain 3: Iteration: 10 / 10 [100%]  (Sampling)
Chain 3: 
Chain 3:  Elapsed Time: 0 seconds (Warm-up)
Chain 3:                0 seconds (Sampling)
Chain 3:                0 seconds (Total)
Chain 3: 

SAMPLING FOR MODEL 'binomial_1par' NOW (CHAIN 4).
Chain 4: 
Chain 4: Gradient evaluation took 1.9e-05 seconds
Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0.19 seconds.
Chain 4: Adjust your expectations accordingly!
Chain 4: 
Chain 4: 
Chain 4: WARNING: No variance estimation is
Chain 4:          performed for num_warmup < 20
Chain 4: 
Chain 4: Iteration: 1 / 10 [ 10%]  (Warmup)
Chain 4: Iteration: 2 / 10 [ 20%]  (Warmup)
Chain 4: Iteration: 3 / 10 [ 30%]  (Warmup)
Chain 4: Iteration: 4 / 10 [ 40%]  (Warmup)
Chain 4: Iteration: 5 / 10 [ 50%]  (Warmup)
Chain 4: Iteration: 6 / 10 [ 60%]  (Sampling)
Chain 4: Iteration: 7 / 10 [ 70%]  (Sampling)
Chain 4: Iteration: 8 / 10 [ 80%]  (Sampling)
Chain 4: Iteration: 9 / 10 [ 90%]  (Sampling)
Chain 4: Iteration: 10 / 10 [100%]  (Sampling)
Chain 4: 
Chain 4:  Elapsed Time: 0 seconds (Warm-up)
Chain 4:                0.003 seconds (Sampling)
Chain 4:                0.003 seconds (Total)
Chain 4: 

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 1).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 2).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 3).

TESTING GRADIENT FOR MODEL 'binomial_1par' NOW (CHAIN 4).
[ FAIL 0 | WARN 0 | SKIP 20 | PASS 1059 ]

══ Skipped tests (20) ══════════════════════════════════════════════════════════
• On CRAN (20): 'test-add_integration.R:541:3',
  'test-example_atrial_fibrillation.R:4:1', 'test-example_bcg_vaccine.R:4:1',
  'test-example_blocker.R:4:1', 'test-example_diabetes.R:4:1',
  'test-example_dietary_fat.R:4:1', 'test-example_hta_psoriasis.R:4:1',
  'test-example_parkinsons.R:4:1', 'test-example_plaque_psoriasis.R:4:1',
  'test-example_smoking.R:4:1', 'test-example_statins.R:4:1',
  'test-example_thrombolytics.R:4:1', 'test-example_transfusion.R:4:1',
  'test-marginal_effects.R:65:1', 'test-nma.R:299:3', 'test-nodesplit.R:264:3',
  'test-plot_nma_data.R:2:1', 'test-posterior_ranks.R:99:1',
  'test-predict.R:110:1', 'test-relative_effects.R:65:1'

[ FAIL 0 | WARN 0 | SKIP 20 | PASS 1059 ]
Deleting unused snapshots:
• plot_nma_data/atrial-fibrillation-network-star.svg
• plot_nma_data/atrial-fibrillation-network.svg
• plot_nma_data/bcg-vaccine-network.svg
• plot_nma_data/blocker-network.svg
• plot_nma_data/diabetes-network.svg
• plot_nma_data/dietary-fat-network.svg
• plot_nma_data/duplicated-agd-arms-network.svg
• plot_nma_data/duplicated-agd-contrasts-network.svg
• plot_nma_data/duplicated-ipd-arms-network.svg
• plot_nma_data/hta-psoriasis-network.svg
• plot_nma_data/ndmm-network.svg
• plot_nma_data/parkinsons-arm-network.svg
• plot_nma_data/parkinsons-contrast-network.svg
• plot_nma_data/parkinsons-mixed-network.svg
• plot_nma_data/plaque-psoriasis-network.svg
• plot_nma_data/smoking-network.svg
• plot_nma_data/statins-network.svg
• plot_nma_data/thrombolytics-dias-network.svg
• plot_nma_data/thrombolytics-network.svg
• plot_nma_data/transfusion-network.svg
> 
> proc.time()
   user  system elapsed 
  56.53    1.23   57.75