crmReporter

The crmReporter package is designed to provide a simple interface between crmPack (and other MCMC packages) and the tidyverse and to augment the reporting facilities provided by crmPack, coda, runjags and other packages relating to MCMC simulation.

Installation

crmReporter is available from GitHub. To install it, use

devtools::install_github("PuzzledFace/crmReporter")

Creating tidy data

Creating tidy data with crmReporter is simple: use the tidy() verb. Tidy works with mcmcs, mcmc.lists, runjagss and runjags.lists.

library(crmReporter)
#> Registered S3 method overwritten by 'crmPack':
#>   method       from  
#>   print.gtable gtable

data("oCRMPosteriorShort")
x <- oCRMPosteriorShort %>% tidy()
x %>% head()
#> # A tibble: 6 x 5
#>   Chain Sample Parameter Index Value
#>   <int> <chr>  <chr>     <int> <dbl>
#> 1     1 5001   alpha         1 7.27 
#> 2     1 5001   alpha         2 3.10 
#> 3     1 5001   beta         NA 0.959
#> 4     1 5003   alpha         1 5.73 
#> 5     1 5003   alpha         2 4.66 
#> 6     1 5003   beta         NA 0.886

You can use the output from tidy() as input to other crmReporter functions or to your own code built within the Tidyverse. Here are some sample outputs from crmReporter functions. They all use data from the first example study in the original O'Quigley paper.

	Number of patients		Status
Dose	Treated	Evaluable	No Tox	DLT
0	0	0	0	0
1	5	5	3	2
2	15	15	11	4
3	3	3	2	1
4	2	2	1	1

					p(Tox)
	Patients					Quantiles
Dose	Treated	Evaluable	No Tox	Tox	Mean	5%	10%	Median	90%	95%
1	5	5	3	2	0.22	0.02	0.16	0.22	0.27	0.67
2	15	15	11	4	0.31	0.05	0.25	0.31	0.37	0.74
3	3	3	2	1	0.44	0.13	0.38	0.44	0.50	0.81
4	2	2	1	1	0.54	0.22	0.48	0.54	0.60	0.85
5	0	0	0	0	0.70	0.42	0.66	0.70	0.74	0.91
6	0	0	0	0	0.83	0.64	0.81	0.83	0.86	0.95

#> Warning: Unknown or uninitialised column: `Parameter`.