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https://github.com/johnmackintosh/spccharter

Creates multiple SPC / process behaviour charts, automatically detecting signals of process change and revising centre lines and control limits. WIP. See {runcharter} for automated run charts
https://github.com/johnmackintosh/spccharter

healthcare nhs nhsr-community quality-control quality-improvement quality-improvement-efforts rdatatable rstats rstats-package statistical-process-control

Last synced: about 2 months ago
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Creates multiple SPC / process behaviour charts, automatically detecting signals of process change and revising centre lines and control limits. WIP. See {runcharter} for automated run charts

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README

        

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```

# spccharter

[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![AppVeyor build status](https://ci.appveyor.com/api/projects/status/github/johnmackintosh/spccharter?branch=master&svg=true)](https://ci.appveyor.com/project/johnmackintosh/spccharter)

[![R-CMD-check](https://github.com/johnmackintosh/spccharter/workflows/R-CMD-check/badge.svg)](https://github.com/johnmackintosh/spccharter/actions)

The goal of spccharter is rapid analysis of multiple statistical process control charts.
The package will create charts, detect signals of improvement, and revise control limits each time a signal occurs.
Currently, 'C', 'P' and 'U' charts can be produced.

The package supports non standard evaluation - you can pass bare variable names.

## Installation

spccharter is not on [CRAN](https://CRAN.R-project.org) yet

*But* the development version is available on [GitHub](https://github.com/) with:

``` r
# install.packages("remotes") # if not already installed
remotes::install_github("johnmackintosh/spccharter")
```
## Example

One grouping variable:

```{r example, eval=FALSE}
library(spccharter)
spccharter(data, numerator = counts, datecol = date,
by = category_1, plot_type = 'c', direction = "both")
```

Two grouping variables:

```{r, eval=FALSE}
library(spccharter)
spccharter(data, numerator = counts, denominator = attends, datecol = date,
by = c('ward','hospital'), plot_type = 'p', direction = "both")
```

## Example plots

![facet-spccharter](https://user-images.githubusercontent.com/3278367/84841170-7a516300-b039-11ea-90fb-9a373ac8bc26.PNG)

![spc-c-chart](https://user-images.githubusercontent.com/3278367/84840888-b932e900-b038-11ea-87d0-2e32e99bcdd1.png)

![spc-pchart](https://user-images.githubusercontent.com/3278367/84840901-c3ed7e00-b038-11ea-9377-b7a564433af0.png)