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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, echo = FALSE}
knitr::opts_chunk$set(
error = FALSE,
warning = FALSE,
message = FALSE,
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
```
# oldr: An Implementation of the Rapid Assessment Method for Older People (RAM-OP) <img src="man/figures/logo.png" width="200" align="right" />
<!-- badges: start -->
[](https://www.repostatus.org/#active)
[](https://lifecycle.r-lib.org/articles/stages.html#stable)
[](https://github.com/rapidsurveys/oldr/actions/workflows/R-CMD-check.yaml)
[](https://github.com/rapidsurveys/oldr/actions/workflows/rhub.yaml)
[](https://github.com/rapidsurveys/oldr/actions/workflows/test-coverage.yaml)
[](https://app.codecov.io/gh/rapidsurveys/oldr)
[](https://www.codefactor.io/repository/github/rapidsurveys/oldr)
[](https://zenodo.org/badge/latestdoi/105472081)
<!-- badges: end -->
[HelpAge International](https://www.helpage.org), [VALID International](http://www.validinternational.org), and [Brixton Health](http://www.brixtonhealth.com), with financial assistance from the [Humanitarian Innovation Fund (HIF)](http://www.elrha.org/hif/home/), have developed a **Rapid Assessment Method for Older People (RAM-OP)** that provides accurate and reliable estimates of the needs of older people. The method uses simple procedures, in a short time frame (i.e. about two weeks including training, data collection, data entry, and data analysis), and at considerably lower cost than other methods. The **RAM-OP** method is based on the following principles:
* Use of a familiar *“household survey”* design employing a two-stage cluster sample design optimised to allow the use of a small primary sample (*m ≥ 16 clusters*) and a small overall (*n ≥ 192*) sample.
* Assessment of multiple dimensions of need in older people (including prevalence of global, moderate and severe acute malnutrition) using, whenever possible, standard and well-tested indicators and question sets.
* Data analysis performed using modern computer-intensive methods to allow estimates of indicator levels to be made with useful precision using a small sample size.
## Installation
You can install `oldr` from [CRAN](https://cran.r-project.org) with:
```{r install-cran, echo = TRUE, eval = FALSE}
install.packages("oldr")
```
You can install the development version of `oldr` from [GitHub](https://github.com/rapidsurveys/oldr) with:
```{r install, eval = FALSE}
if(!require(remotes)) install.packages("remotes")
remotes::install_github("rapidsurveys/oldr")
```
## Usage
This package contains functions that support in the data processing, analysis and visualisation of RAM-OP survey datasets collected using the standard RAM-OP survey questionnaire.
The figure below illustrates the RAM-OP workflow and indicates which functions in the `oldr` package support which particular step in the process.
```{r ramOPworkflow, echo = FALSE, eval = FALSE, fig.width = 8, fig.height = 10, fig.align = "center"}
DiagrammeR::grViz("
digraph ramOP {
# a 'graph' statement
graph [overlap = false, fontsize = 14, fontname = Helvetica]
# Terminal nodes
node [shape = oval, width = 1.5, penwidth = 2, fontsize = 14]
a [label = '@@1'; color = darkgreen; fontcolor = darkgreen];
n [label = '@@14'; color = crimson; fontcolor = crimson];
# Input/output nodes
node [shape = parallelogram, fixedsize = true, height = 1, width = 1.5,
penwidth = 2, color = royalblue1, fontcolor = royalblue1]
b [label = '@@2'];
l [label = '@@12']
# Process nodes
node [shape = rect]
d [label = '@@4'];
g [label = '@@7'];
h [label = '@@8'];
j [label = '@@10'];
# Package nodes
node [shape = oval, fixedsize = TRUE, width = 2.5, penwidth = 2,
fontsize = 14, fontname = Courier, color = darkviolet,
fontcolor = darkviolet]
c [label = '@@3';];
e [label = '@@5';];
f [label = '@@6'];
i [label = '@@9'];
k [label = '@@11'];
m [label = '@@13'];
edge [minlen = 2, arrowsize = 0.75, penwidth = 2, color = dimgray]
a -> b
b -> d
d -> g
d -> h
g -> j
h -> j
j -> l
l -> n
edge [minlen = 3]
b -> c
c -> b
d -> e
e -> d
f -> g
g -> f
h -> i
i -> h
j -> k
k -> j
l -> m
m -> l
subgraph {
rank = same; b; c;
}
subgraph {
rank = same; d; e;
}
subgraph {
rank = same; f; g; h; i;
}
subgraph {
rank = same; j; k
}
subgraph {
rank = same; l; m;
}
}
[1]: 'START'
[2]: 'Collect\\ndata'
[3]: 'EpiData\\nor\\nOpen Data Kit'
[4]: 'Process\\nand\\nrecode\\ndata'
[5]: 'create_op_\\nfunctions'
[6]: 'estimate_classic'
[7]: 'Estimate\\nindicators'
[8]: 'Estimate\\nanthropometric\\nindicators'
[9]: 'estimate_probit'
[10]: 'Visualise\\nestimates'
[11]: 'chart_\\nfunctions'
[12]: 'Report\\nestimates'
[13]: 'report_op_\\nfunctions'
[14]: 'END'
"
)
```
```{r workflow, echo = FALSE, eval = TRUE, fig.align = "center", out.width = "80%"}
knitr::include_graphics("man/figures/ramOPworkflow.png")
```
For a more detailed description of the RAM-OP survey, read the [RAM-OP manual](https://rapidsurveys.io/ramOPmanual/).
## Citation
If you find the `oldr` package useful, please cite using the suggested citation provided by a call to the `citation` function as follows:
```{r cite}
citation("oldr")
```
## Community guidelines
Feedback, bug reports, and feature requests are welcome; file issues or seek support [here](https://github.com/rapidsurveys/oldr/issues). If you would like to contribute to the package, please see our [contributing guidelines](https://rapidsurveys.io/oldr/CONTRIBUTING.html).
This project is released with a [Contributor Code of Conduct](https://rapidsurveys.io/oldr/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.