Reliability, Validity, and Usability of Data Extraction Programs for Single-Case Research Designs.
Use the free WebPlotDigitizer to copy single-case graph data quickly and accurately.
01Research in Context
What this study did
Moeyaert et al. (2016) tested how well four computer programs pull numbers from single-case graphs.
They asked volunteers to copy data points from published line graphs and checked speed, mistakes, and ease of use.
The goal was to see which tool you can trust when you need to re-analyze old charts.
What they found
No program gave clearly cleaner data than the others.
WebPlotDigitizer scored highest for speed and ease, and it is free.
Ungraph also did well, but you have to pay for it.
How this fits with other research
Lanovaz et al. (2020) also focus on single-case methods, but they looked at how many tiers you need in a multiple baseline instead of how to grab the data.
Cariveau et al. (2021) give step-by-step tech tips like Mariola, yet their guide is for building iPad tasks in PowerPoint, not for pulling numbers from graphs.
Antonak (1990) reviewed an old Macintosh graphing tool; Mariola’s picks replace that outdated software with modern, cross-platform options.
Why it matters
If you meta-analyze single-case studies, you can skip pricey software. Download WebPlotDigitizer, spend five minutes on the tutorial, and start copying data with confidence. Your students will thank you for the free tip, and your error rate will stay low.
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02At a glance
03Original abstract
Single-case experimental designs (SCEDs) have been increasingly used in recent years to inform the development and validation of effective interventions in the behavioral sciences. An important aspect of this work has been the extension of meta-analytic and other statistical innovations to SCED data. Standard practice within SCED methods is to display data graphically, which requires subsequent users to extract the data, either manually or using data extraction programs. Previous research has examined issues of reliability and validity of data extraction programs in the past, but typically at an aggregate level. Little is known, however, about the coding of individual data points. We focused on four different software programs that can be used for this purpose (i.e., Ungraph, DataThief, WebPlotDigitizer, and XYit), and examined the reliability of numeric coding, the validity compared with real data, and overall program usability. This study indicates that the reliability and validity of the retrieved data are independent of the specific software program, but are dependent on the individual single-case study graphs. Differences were found in program usability in terms of user friendliness, data retrieval time, and license costs. Ungraph and WebPlotDigitizer received the highest usability scores. DataThief was perceived as unacceptable and the time needed to retrieve the data was double that of the other three programs. WebPlotDigitizer was the only program free to use. As a consequence, WebPlotDigitizer turned out to be the best option in terms of usability, time to retrieve the data, and costs, although the usability scores of Ungraph were also strong.
Behavior modification, 2016 · doi:10.1177/0145445516645763