-
Notifications
You must be signed in to change notification settings - Fork 3
Expand file tree
/
Copy pathREADME.Rmd
More file actions
54 lines (39 loc) · 1.32 KB
/
README.Rmd
File metadata and controls
54 lines (39 loc) · 1.32 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# c212: Methods for Detecting Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes)
<!-- badges: start -->
<!-- badges: end -->
The goal of c212 is to provide a self-contained set of methods, which use groupings of adverse events, to aid clinical trial safety investigators, statisticians and researchers, in the early detection of adverse events.
## Installation
You can install the released version of c212 from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("c212")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("rcarragh/c212")
```
## Example
This is a basic example which shows how to apply the Double False Discovery Rate to a set of multiple hypotheses:
```{r example1}
library(c212)
data(c212.FDR.data)
c212.err.cntrl(c212.FDR.data, method="DFDR", alpha = 0.05)
```
This is an example of how to apply the Berry and Berry model:
```{r example2}
library(c212)
data(c212.trial.data)
mod.BB <- c212.BB(c212.trial.data, burnin = 100, iter = 200)
```