Rapid Assessment Method for Older People (RAM-OP)

After a little more than 7 years, we are pleased to announce the first CRAN release of the {oldr} package. {oldr} is an implementation of the Rapid Assessment Method for Older People or RAM-OP. HelpAge International, VALID International, and Brixton Health, with financial assistance from the Humanitarian Innovation Fund (HIF), developed 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.

The {oldr} package is meant to serve as an alternative to the original software developed for RAM-OP. The original software, also built on R using the R AnalyticFlow integrated development environment (IDE), is very useful but is limited by known issues and limitations of the R AnalyticFlow IDE. The {oldr} package, on the other hand, is aimed at experienced R users who may prefer to use their own IDE when implementing a RAM-OP survey. With a few lines of code using {oldr} functions, a user can replicate everything that the original software can do. For example, using the testSVY and testPSU RAM-OP dataset included in the package, a full data processing, analysis, and reporting can be performed as follows:

library(oldr)

testSVY |>
  create_op() |>
  estimate_op(w = testPSU) |>
  report_op_html(
    svy = testSVY, filename = file.path(tempdir(), "ramOPreport")
  )

To learn more about the {oldr} package, see the website.