giabaio · giabaio · Jul 21, 2020 · May 17, 2020 · May 17, 2020 · May 18, 2020
diff --git a/..travis.yml.swp b/..travis.yml.swp
diff --git a/.Rbuildignore b/.Rbuildignore
@@ -2,3 +2,4 @@
 ^\.Rproj\.user$
 ^\.travis\.yml$
 ^appveyor\.yml$
+^LICENSE\.md$
diff --git a/.gitignore b/.gitignore
@@ -3,3 +3,4 @@
 .RData
 .Ruserdata
 *.Rproj
+inst/doc
diff --git a/BCEA.Rproj b/BCEA.Rproj
@@ -15,4 +15,4 @@ LaTeX: pdfLaTeX
 BuildType: Package
 PackageUseDevtools: Yes
 PackageInstallArgs: --no-multiarch --with-keep.source
-PackageRoxygenize: rd,collate
+PackageRoxygenize: rd,collate,vignette
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -31,11 +31,12 @@ Suggests:
 Imports: MASS, dplyr, rlang
 Additional_repositories: https://inla.r-inla-download.org/R/stable/
 Description: Produces an economic evaluation of a Bayesian model in the form of MCMC simulations. Given suitable variables of cost and effectiveness / utility for two or more interventions, This package computes the most cost-effective alternative and produces graphical summaries and probabilistic sensitivity analysis.
-License: GPL (>=2)
+License: GPL-3
 URL: http://www.statistica.it/gianluca/BCEA,
      http://www.statistica.it/gianluca,
      https://github.com/giabaio/BCEA    
 Depends: R (>= 2.10)
 NeedsCompilation: no
-RoxygenNote: 6.1.1
+RoxygenNote: 7.1.0
 Encoding: UTF-8
+VignetteBuilder: knitr
diff --git a/LICENSE b/LICENSE
@@ -0,0 +1,2 @@
+YEAR: 2020
+COPYRIGHT HOLDER: G Baio
diff --git a/LICENSE.md b/LICENSE.md
diff --git a/NAMESPACE b/NAMESPACE
@@ -12,7 +12,7 @@ S3method(bcea, default)
 S3method(evppi, default)
 export(BCEAweb)
 export(CEriskav)
-export(CreateInputs)
+export(createInputs)
 export(bcea)
 export(ceac.plot)
 export(ceaf.plot)
@@ -26,7 +26,6 @@ export(evi.plot)
 export(evppi)
 export(ib.plot)
 export(info.rank)
-export(mce.plot)
 export(mixedAn)
 export(multi.ce)
 export(plot.CEriskav)

diff --git a/NEWS.md b/NEWS.md
@@ -0,0 +1,120 @@
+# BCEA 2.3-2
+
+* Added a `NEWS.md` file to track changes to the package.
+* Major refactoring of code base
+* Testing suite written
+
+## Feature updates
+
+* Deprecated `mce.plot()`. Now dispatched on `ceac.plot()` for both `multi.ce()` and `bcea()` outputs.
+* `new_bcea()` constructor
+
+
+## Fixes
+
+# BCEA 2.3-1.1
+26 Aug 2019
+
+# BCEA 2.3-1<sup>^</sup>
+
+# BCEA 2.2-6<sup>^</sup>
+* Fix in `evppi` to allow N to be selected in all methods
+* Fix `diag.evppi`
+
+# BCEA 2.2-5<sup>^</sup>
+
+* Some changes to EVPPI
+
+# BCEA v2.2.4
+Nov 2016
+
+* Fixes for new ggplot2 version (`legend.spacing()` and `plot.title` hjust argument)
+
+# BCEA 2.2-3<sup>^</sup>
+May 2016
+
+* Major update for the EVPPI to include PFC
+* Fixed issues with info.rank
+
+# BCEA 2.2-2<sup>^</sup>
+January 2016
+
+* Minor change to `ceef.plot` to align with ggplot2 v2.0.0
+
+# BCEA v2.2.1
+October 2015
+
+* Adds the info-rank plot
+
+# BCEA v2.2
+October 2015
+
+* Cleaned up and aligned with R's settings
+* `EVPPI` function polished up
+
+# BCEA 2.1-1<sup>^</sup>
+April/July 2015
+
+* New function for EVPPI using SPDE-INLA
+* Modifications to the EVPPI functions 
+* Documentation updated
+* Allows xlim & ylim in the `ceplane.plot`, `contour` and `contour2` functions
+* It is now possible to run bcea for a scalar wtp
+* Old evppi function and method has been renamed `evppi0`, which means there's also a new `plot.evppi0` method
+
+# BCEA 2.1-0<sup>^</sup>
+October 2014
+
+* Migrated from `if(require())` to `if(requireNamespace(,quietly=TRUE))`
+* Documentation updated
+* Added threshold argument to `ceef.plot` function
+
+# BCEA v2.1.0-pre2
+October 2014
+
+* modifications to `ceef.plot`, `createInputs`, `struct.psa`
+
+# BCEA v2.1-0-pre1
+September 2014
+
+* Documentation updated
+* Smoking dataset and `ceef.plot` function included, additional modifications
+
+# BCEA v2.0-2c
+July, 2014
+
+# BCEA v2.0-2b
+February 2014
+
+* `ceac.plot` and `eib.plot`: option comparison included for base graphics
+
+# BCEA 2.0-2<sup>^</sup>
+November 2013
+
+# BCEA 2.0-1<sup>^</sup>
+July, 2013
+
+# BCEA 2.0<sup>^</sup>
+
+## Feature updates
+
+* Implements two quick and general methods to compute the EVPPI
+* Function `CreateInputs()`, which takes as input an object in the class rjags or bugs
+* Compute the EVPPI for one or more parameters calling the function `evppi()`
+* Results can be visualised using the specific method plot for the class evppi and show the overall EVPI with the EVPPI for the selected parameter(s)
+
+# BCEA 1.3-1
+
+# BCEA 1.3-0<sup>^</sup>
+June 2013
+
+# BCEA 1.2
+17 September 2012
+
+# BCEA 1.1.1<sup>^</sup>
+
+# BCEA 1.1<sup>^</sup>
+14 September 2012
+
+# BCEA 1.0<sup>^</sup>
+4 January 2012
diff --git a/R/BCEA-package.R b/R/BCEA-package.R
@@ -1,5 +1,4 @@
 
-
 #' BCEA: A package for Bayesian Cost-Effectiveness Analysis
 #' 
 #' A package to post-process the results of a Bayesian health economic model
@@ -12,163 +11,29 @@
 #' variables of costs and clinical benefits for two or more interventions,
 #' produces a health economic evaluation. Compares one of the interventions
 #' (the "reference") to the others ("comparators"). Produces many summary and
-#' plots to analyse the results
+#' plots to analyse the results.
 #' 
-#' @name BCEA-package
 #' @aliases BCEA-package BCEA
-#' @docType package
+#' 
 #' @author Gianluca Baio, Andrea Berardi, Anna Heath
+#' #' Maintainer: Gianluca Baio <gianluca@@stats.ucl.ac.uk>
 #' 
-#' Maintainer: Gianluca Baio <gianluca@@stats.ucl.ac.uk>
 #' @references Baio, G., Dawid, A. P. (2011). Probabilistic Sensitivity
 #' Analysis in Health Economics.  Statistical Methods in Medical Research
 #' doi:10.1177/0962280211419832.
 #' 
 #' Baio G. (2012). Bayesian Methods in Health Economics. CRC/Chapman Hall,
-#' London
+#' London.
 #' 
 #' Baio G., Berardi A., Heath A. (forthcoming). Bayesian Cost Effectiveness
 #' Analysis with the R package BCEA. Springer
 #' @keywords Bayesian models Health economic evaluation
-NULL
-
-
-
-
-
-#' Data set for the Bayesian model for the cost-effectiveness of smoking
-#' cessation interventions
-#' 
-#' This data set contains the results of the Bayesian analysis used to model
-#' the clinical output and the costs associated with the health economic
-#' evaluation of four different smoking cessation interventions.
-#' 
-#' 
-#' @name Smoking
-#' @aliases Smoking data life.years pi smoking smoking_output
-#' @docType data
-#' @format A data list including the variables needed for the smoking cessation
-#' cost-effectiveness analysis. The variables are as follows: \describe{
-#' \item{list("c")}{a matrix of 500 simulations from the posterior distribution
-#' of the overall costs associated with the four strategies}
-#' \item{list("data")}{a dataset containing the characteristics of the smokers
-#' in the UK population} \item{list("e")}{a matrix of 500 simulations from the
-#' posterior distribution of the clinical benefits associated with the four
-#' strategies} \item{list("life.years")}{a matrix of 500 simulations from the
-#' posterior distribution of the life years gained with each strategy}
-#' \item{list("pi")}{a matrix of 500 simulations from the posterior
-#' distribution of the event of smoking cessation with each strategy}
-#' \item{list("smoking")}{a data frame containing the inputs needed for the
-#' network meta-analysis model. The \code{data.frame} object contains:
-#' \code{nobs}: the record ID number, \code{s}: the study ID number, \code{i}:
-#' the intervention ID number, \code{r_i}: the number of patients who quit
-#' smoking, \code{n_i}: the total number of patients for the row-specific arm
-#' and \code{b_i}: the reference intervention for each study}
-#' \item{list("smoking_output")}{a \code{rjags} object obtained by running the
-#' network meta-analysis model based on the data contained in the
-#' \code{smoking} object} \item{list("smoking_mat")}{a matrix obtained by
-#' running the network meta-analysis model based on the data contained in the
-#' \code{smoking} object} \item{list("treats")}{a vector of labels associated
-#' with the four strategies} }
-#' @references Baio G. (2012). Bayesian Methods in Health Economics.
-#' CRC/Chapman Hall, London
-#' @source Effectiveness data adapted from Hasselblad V. (1998). Meta-analysis
-#' of Multitreatment Studies. Medical Decision Making 1998;18:37-43.
-#' 
-#' Cost and population characteristics data adapted from various sources:
-#' \itemize{ \item Taylor, D.H. Jr, et al. (2002). Benefits of smoking
-#' cessation on longevity. American Journal of Public Health 2002;92(6) \item
-#' ASH: Action on Smoking and Health (2013). ASH fact sheet on smoking
-#' statistics, \cr \code{http://ash.org.uk/files/documents/ASH_106.pdf} \item
-#' Flack, S., et al. (2007). Cost-effectiveness of interventions for smoking
-#' cessation. York Health Economics Consortium, January 2007 \item McGhan,
-#' W.F.D., and Smith, M. (1996). Pharmacoeconomic analysis of smoking-cessation
-#' interventions. American Journal of Health-System Pharmacy 1996;53:45-52 }
-#' @keywords datasets
-#' @examples
-#' 
-#' data(Smoking)
-#' 
-#' \donttest{
-#' m=bcea(e,c,ref=4,interventions=treats,Kmax=500)
-#' }
-#' 
-NULL
-
-
-
-
-
-#' Data set for the Bayesian model for the cost-effectiveness of influenza
-#' vaccination
-#' 
-#' This data set contains the results of the Bayesian analysis used to model
-#' the clinical output and the costs associated with an influenza vaccination.
-#' 
-#' 
-#' @name Vaccine
-#' @aliases Vaccine c cost.GP cost.hosp cost.otc cost.time.off cost.time.vac
-#' cost.travel cost.trt1 cost.trt2 cost.vac e N N.outcomes N.resources
-#' QALYs.adv QALYs.death QALYs.hosp QALYs.inf QALYs.pne treats vaccine
-#' @docType data
-#' @format A data list including the variables needed for the influenza
-#' vaccination.  The variables are as follows:
-#' 
-#' \describe{ \item{list("c")}{a matrix of simulations from the posterior
-#' distribution of the overall costs associated with the two treatments}
-#' \item{list("cost.GP")}{a matrix of simulations from the posterior
-#' distribution of the costs for GP visits associated with the two treatments}
-#' \item{list("cost.hosp")}{a matrix of simulations from the posterior
-#' distribution of the costs for hospitalisations associated with the two
-#' treatments} \item{list("cost.otc")}{a matrix of simulations from the
-#' posterior distribution of the costs for over-the-counter medications
-#' associated with the two treatments} \item{list("cost.time.off")}{a matrix of
-#' simulations from the posterior distribution of the costs for time off work
-#' associated with the two treatments} \item{list("cost.time.vac")}{a matrix of
-#' simulations from the posterior distribution of the costs for time needed to
-#' get the vaccination associated with the two treatments}
-#' \item{list("cost.travel")}{a matrix of simulations from the posterior
-#' distribution of the costs for travel to get vaccination associated with the
-#' two treatments} \item{list("cost.trt1")}{a matrix of simulations from the
-#' posterior distribution of the overall costs for first line of treatment
-#' associated with the two interventions} \item{list("cost.trt2")}{a matrix of
-#' simulations from the posterior distribution of the overall costs for second
-#' line of treatment associated with the two interventions}
-#' \item{list("cost.vac")}{a matrix of simulations from the posterior
-#' distribution of the costs for vaccination} \item{list("e")}{a matrix of
-#' simulations from the posterior distribution of the clinical benefits
-#' associated with the two treatments} \item{list("N")}{the number of subjects
-#' in the reference population} \item{list("N.outcomes")}{the number of
-#' clinical outcomes analysed} \item{list("N.resources")}{the number of
-#' health-care resources under study} \item{list("QALYs.adv")}{a vector from
-#' the posterior distribution of the QALYs associated with advert events}
-#' \item{list("QALYs.death")}{a vector from the posterior distribution of the
-#' QALYs associated with death} \item{list("QALYs.hosp")}{a vector from the
-#' posterior distribution of the QALYs associated with hospitalisation}
-#' \item{list("QALYs.inf")}{a vector from the posterior distribution of the
-#' QALYs associated with influenza infection} \item{list("QALYs.pne")}{a vector
-#' from the posterior distribution of the QALYs associated with penumonia}
-#' \item{list("treats")}{a vector of labels associated with the two treatments}
-#' \item{list("vaccine")}{a \code{rjags} object containing the simulations for
-#' the parameters used in the original model} \item{list("vaccine_mat")}{a
-#' matrix containing the simulations for the parameters used in the original
-#' model} }
-#' @references Baio, G., Dawid, A. P. (2011). Probabilistic Sensitivity
-#' Analysis in Health Economics.  Statistical Methods in Medical Research
-#' doi:10.1177/0962280211419832.
-#' @source Adapted from Turner D, Wailoo A, Cooper N, Sutton A, Abrams K,
-#' Nicholson K.  The cost-effectiveness of influenza vaccination of healthy
-#' adults 50-64 years of age.  Vaccine. 2006;24:1035-1043.
-#' @keywords datasets
-#' @examples
 #' 
-#' data(Vaccine)
-#' 
-#' \donttest{
-#' m=bcea(e,c,ref=1,interventions=treats)
-#' }
+#' @docType package
+#' @name BCEA-package
 #' 
+#' @import dplyr
+#' @import ggplot2
+#' @import purrr
+#' @import reshape2
 NULL
-
-
-
diff --git a/R/BCEAweb.R b/R/BCEAweb.R
@@ -39,9 +39,9 @@ BCEAweb <- function(e=NULL,c=NULL,parameters=NULL,...) {
   if(exists("launch.browser",exArgs)) {launch.browser=exArgs$launch.browser} else {launch.browser=TRUE}
 
   # This makes the possible inputs available to the webapp!
-  # First uses BCEA::CreateInputs to process the simulations for the model parameters
+  # First uses BCEA::createInputs to process the simulations for the model parameters
   #  (this means the user can pass a BUGS, JAGS, Stan, or xls object and BCEA will know what to do. Also eliminates need with further dependencies).
-  if(!is.null(parameters)){parameters=CreateInputs(parameters)$mat} 
+  if(!is.null(parameters)){parameters = createInputs(parameters)$mat} 
   if(!is.null(e)){e=as.matrix(e)}
   if(!is.null(c)){c=as.matrix(c)}
 

diff --git a/R/CEriskav.R b/R/CEriskav.R
@@ -1,12 +1,9 @@
-###CEriskav###################################################################################################
-
 
 #' Cost-effectiveness analysis including a parameter of risk aversion
 #' 
 #' Extends the standard cost-effectiveness analysis to modify the utility
 #' function so that risk aversion of the decision maker is explicitly accounted
-#' for
-#' 
+#' for. 
 #' 
 #' @aliases CEriskav CEriskav.default
 #' @param he A \code{bcea} object containing the results of the Bayesian