---
title: "Cost-Effectiveness Efficiency Frontier"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Cost-Effectiveness Efficiency Frontier}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---
  
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width = 6
)
```

```{r setup, results='hide', message=FALSE, warning=FALSE, echo=FALSE}
library(BCEA)
library(dplyr)
library(reshape2)
library(ggplot2)
library(purrr)
```

## Introduction

The line connecting successive points on a cost-effectiveness plane which each
represent the effect and cost associated with different treatment alternatives.
The gradient of a line segment represents the ICER of the treatment comparison
between the two alternatives represented by that segment.
The cost-effectiveness frontier consists of the set of points corresponding to
treatment alternatives that are considered to be cost-effective at different values
of the cost-effectiveness threshold. The steeper the gradient between successive
points on the frontier, the higher is the ICER between these treatment alternatives
and the more expensive alternative would be considered cost-effective only when a
high value of the cost-effectiveness threshold is assumed.
Points not lying on the cost-effectiveness frontier represent treatment alternatives
that are not considered cost-effective at any value of the cost-effectiveness threshold.

## R code

To create the plots in BCEA we first call the `bcea()` function.

```{r}
data(Smoking)

treats <- c("No intervention", "Self-help", "Individual counselling", "Group counselling")
bcea_smoke <- bcea(eff, cost, ref = 4, interventions = treats, Kmax = 500)
```

* base R

```{r}
# all interventions
ceef.plot(bcea_smoke)

# subset
setComparisons(bcea_smoke) <- c(1,3)
ceef.plot(bcea_smoke)

# check numbering and legend
setComparisons(bcea_smoke) <- c(3,1)
ceef.plot(bcea_smoke)

setComparisons(bcea_smoke) <- c(3,2)
ceef.plot(bcea_smoke)

setComparisons(bcea_smoke) <- 1
ceef.plot(bcea_smoke)

# add interventions back in
setComparisons(bcea_smoke) <- c(1,3)
ceef.plot(bcea_smoke)
```

* ggplot

```{r error=TRUE}
bcea_smoke <- bcea(eff, cost, ref = 4, interventions = treats, Kmax = 500)

# all interventions
ceef.plot(bcea_smoke, graph = "ggplot")

# subset
setComparisons(bcea_smoke) <- c(1,3)
ceef.plot(bcea_smoke, graph = "ggplot")

# check numbering and legend
setComparisons(bcea_smoke) <- c(3,1)
ceef.plot(bcea_smoke, graph = "ggplot")

setComparisons(bcea_smoke) <- c(3,2)
ceef.plot(bcea_smoke, graph = "ggplot")

setComparisons(bcea_smoke) <- 1
ceef.plot(bcea_smoke, graph = "ggplot")

# add interventions back in
setComparisons(bcea_smoke) <- c(1,3)
ceef.plot(bcea_smoke, graph = "ggplot")
```

Check legend position argument:

```{r error=TRUE}
# base R
ceef.plot(bcea_smoke, pos = c(1,0))
ceef.plot(bcea_smoke, pos = c(1,1))

ceef.plot(bcea_smoke, pos = TRUE)
ceef.plot(bcea_smoke, pos = FALSE)

ceef.plot(bcea_smoke, pos = "topleft")
ceef.plot(bcea_smoke, pos = "topright")
ceef.plot(bcea_smoke, pos = "bottomleft")
ceef.plot(bcea_smoke, pos = "bottomright")

# ggplot2
ceef.plot(bcea_smoke, graph = "ggplot", pos = c(1,0))
ceef.plot(bcea_smoke, graph = "ggplot", pos = c(1,1))

ceef.plot(bcea_smoke, graph = "ggplot", pos = TRUE)
ceef.plot(bcea_smoke, graph = "ggplot", pos = FALSE)

ceef.plot(bcea_smoke, graph = "ggplot", pos = "top")
ceef.plot(bcea_smoke, graph = "ggplot", pos = "bottom")
ceef.plot(bcea_smoke, graph = "ggplot", pos = "left")
ceef.plot(bcea_smoke, graph = "ggplot", pos = "right")
```

### Flipping plot

```{r error=TRUE}
ceef.plot(bcea_smoke,
          flip = TRUE,
          dominance = FALSE,
          start.from.origins = FALSE,
          print.summary = FALSE,
          graph = "base")

ceef.plot(bcea_smoke,
          dominance = TRUE,
          start.from.origins = FALSE,
          pos = TRUE,
          print.summary = FALSE,
          graph = "ggplot2")
```


### Start from origin or smallest (e,c).

```{r error=TRUE}
ceef.plot(bcea_smoke,
          flip = TRUE,
          dominance = TRUE,
          start.from.origins = TRUE,
          print.summary = FALSE,
          graph = "base")

ceef.plot(bcea_smoke,
          dominance = TRUE,
          start.from.origins = TRUE,
          pos = TRUE,
          print.summary = FALSE,
          graph = "ggplot2")
```

### Negative cost or effectiveness

```{r error=TRUE}
data("Smoking")

cost[, 4] <- -cost[, 4]
bcea_smoke <- bcea(eff, cost, ref = 3, interventions = treats, Kmax = 500)

# all interventions
ceef.plot(bcea_smoke, graph = "ggplot")
ceef.plot(bcea_smoke, graph = "base")

ceef.plot(bcea_smoke, start.from.origins = TRUE, graph = "ggplot")
ceef.plot(bcea_smoke, start.from.origins = TRUE, graph = "base")

setComparisons(bcea_smoke) <- c(1,2)
ceef.plot(bcea_smoke, graph = "ggplot")
ceef.plot(bcea_smoke, graph = "base")

eff[, 3] <- -eff[, 3]
bcea_smoke <- bcea(eff, cost, ref = 3, interventions = treats, Kmax = 500)
ceef.plot(bcea_smoke, graph = "ggplot")
ceef.plot(bcea_smoke, graph = "base")


data("Smoking")
eff[, 3] <- -eff[, 3]
bcea_smoke <- bcea(eff, cost, ref = 3, interventions = treats, Kmax = 500)
ceef.plot(bcea_smoke, graph = "ggplot")
ceef.plot(bcea_smoke, graph = "base")
```


```{r eval=FALSE, echo=FALSE}
# create output docs
rmarkdown::render(input = "vignettes/ceef.Rmd", output_format = "pdf_document", output_dir = "vignettes")
rmarkdown::render(input = "vignettes/ceef.Rmd", output_format = "html_document", output_dir = "vignettes")
```
