tests/testthat/_snaps/mcmc.md

In basket: Basket Trial Analysis

MCMC can be calculated correctly.

Code
  unclass(summary(mcmc_res1))
Output
  $call
  mem_mcmc(responses = vemu_wide1$responders, size = vemu_wide1$evaluable, 
      name = vemu_wide1$baskets, p0 = 0.15, mcmc_iter = 100, mcmc_burnin = 100, 
      cluster_analysis = TRUE)

  $basket

  The Null Response Rates (alternative is greater):
                 NSCLC ECD or LCH   ATC
  Null            0.15       0.15 0.150
  Posterior Prob  1.00       1.00 0.996

  Posterior Mean and Median Response Rates:
         NSCLC ECD or LCH   ATC
  Mean   0.405      0.405 0.397
  Median 0.404      0.403 0.397

  Highest Posterior Density Interval with Coverage Probability 0.95:
              NSCLC ECD or LCH   ATC
  Lower Bound 0.250      0.253 0.233
  Upper Bound 0.556      0.556 0.563

  Posterior Effective Sample Size:
   NSCLC ECD or LCH   ATC
   38.34     38.766 32.36


  $cluster

  Cluster 1                           
   "NSCLC" "ECD or LCH" "ATC"

  The Null Response Rates (alternative is greater):
                             Cluster 1
  Posterior for null of 0.15     0.999

  Posterior Mean and Median Response Rates:
         Cluster 1
  Mean       0.402
  Median     0.401

  Highest Posterior Density Interval with Coverage Probability 0.95:
              Cluster 1
  Lower Bound     0.248
  Upper Bound     0.561

  Posterior Effective Sample Size:
   Cluster 1
      36.304

Exact corner case models

Code
  summary(mem_mcmc(responses = c(4, 3, 0), size = c(10, 3, 0), name = letters[1:3],
  cluster_analysis = TRUE, mcmc_iter = 100, mcmc_burnin = 100, p0 = 0.25))
Output

  -- The MEM Model Call ----------------------------------------------------------

  mem_mcmc(responses = c(4, 3, 0), size = c(10, 3, 0), name = letters[1:3], 
      p0 = 0.25, mcmc_iter = 100, mcmc_burnin = 100, cluster_analysis = TRUE)

  -- The Basket Summary ----------------------------------------------------------

  The Null Response Rates (alternative is greater):
                     a     b     c
  Null           0.250 0.250 0.250
  Posterior Prob 0.867 0.997 0.852

  Posterior Mean and Median Response Rates:
             a     b     c
  Mean   0.414 0.862 0.602
  Median 0.408 0.927 0.603

  Highest Posterior Density Interval with Coverage Probability 0.95:
                  a    b     c
  Lower Bound 0.148 0.51 0.056
  Upper Bound 0.694 1.00 1.000

  Posterior Effective Sample Size:
        a     b     c
   11.042 5.602 1.947

  -- The Cluster Summary ---------------------------------------------------------

  Cluster 1    
   "a"
  Cluster 2    
   "b"
  Cluster 3    
   "c"

  The Null Response Rates (alternative is greater):
                             Cluster 1 Cluster 2 Cluster 3
  Posterior for null of 0.25     0.867     0.997     0.852

  Posterior Mean and Median Response Rates:
         Cluster 1 Cluster 2 Cluster 3
  Mean       0.414     0.862     0.602
  Median     0.408     0.927     0.603

  Highest Posterior Density Interval with Coverage Probability 0.95:
              Cluster 1 Cluster 2 Cluster 3
  Lower Bound     0.148      0.51     0.056
  Upper Bound     0.694      1.00     1.000

  Posterior Effective Sample Size:
   Cluster 1 Cluster 2 Cluster 3
      11.042     5.602     1.947

Code
  summary(mem_mcmc(responses = c(4, 3), size = c(10, 3), name = letters[1:2],
  cluster_analysis = TRUE, mcmc_iter = 100, mcmc_burnin = 100, p0 = 0.25))
Output

  -- The MEM Model Call ----------------------------------------------------------

  mem_mcmc(responses = c(4, 3), size = c(10, 3), name = letters[1:2], 
      p0 = 0.25, mcmc_iter = 100, mcmc_burnin = 100, cluster_analysis = TRUE)

  -- The Basket Summary ----------------------------------------------------------

  The Null Response Rates (alternative is greater):
                     a     b
  Null           0.250 0.250
  Posterior Prob 0.871 0.997

  Posterior Mean and Median Response Rates:
             a     b
  Mean   0.417 0.851
  Median 0.412 0.921

  Highest Posterior Density Interval with Coverage Probability 0.95:
                  a     b
  Lower Bound 0.146 0.483
  Upper Bound 0.695 1.000

  Posterior Effective Sample Size:
        a     b
   10.916 5.321

  -- The Cluster Summary ---------------------------------------------------------

  Cluster 1    
   "a"
  Cluster 2    
   "b"

  The Null Response Rates (alternative is greater):
                             Cluster 1 Cluster 2
  Posterior for null of 0.25     0.871     0.997

  Posterior Mean and Median Response Rates:
         Cluster 1 Cluster 2
  Mean       0.417     0.851
  Median     0.412     0.921

  Highest Posterior Density Interval with Coverage Probability 0.95:
              Cluster 1 Cluster 2
  Lower Bound     0.146     0.483
  Upper Bound     0.695     1.000

  Posterior Effective Sample Size:
   Cluster 1 Cluster 2
      10.916     5.321

Code
  summary(mem_mcmc(responses = c(4, 3), size = c(10, 3), name = letters[1:2],
  cluster_analysis = FALSE, mcmc_iter = 100, mcmc_burnin = 100, p0 = 0.25))
Output

  -- The MEM Model Call ----------------------------------------------------------

  mem_mcmc(responses = c(4, 3), size = c(10, 3), name = letters[1:2], 
      p0 = 0.25, mcmc_iter = 100, mcmc_burnin = 100, cluster_analysis = FALSE)

  -- The Basket Summary ----------------------------------------------------------

  The Null Response Rates (alternative is greater):
                     a     b
  Null           0.250 0.250
  Posterior Prob 0.871 0.997

  Posterior Mean and Median Response Rates:
             a     b
  Mean   0.417 0.851
  Median 0.412 0.921

  Highest Posterior Density Interval with Coverage Probability 0.95:
                  a     b
  Lower Bound 0.146 0.483
  Upper Bound 0.695 1.000

  Posterior Effective Sample Size:
        a     b
   10.916 5.321

basket documentation built on Oct. 17, 2021, 1:07 a.m.