Validity and Reliability Analysis of the PlotDigitizer Software Program for Data Extraction from Single-Case Graphs
PlotDigitizer is a free, cross-platform tool that reliably extracts data from single-case graphs with near-perfect accuracy.
01Research in Context
What this study did
Aydin et al. (2022) tested how well PlotDigitizer pulls numbers from single-case graphs.
They compared the extracted points to the original data many times. The goal was to see if the free tool gives the same results every time.
What they found
The match between the first and second extraction was almost perfect. The same coder and different coders got the same numbers.
PlotDigitizer proved both reliable and valid for turning graph lines into usable data.
How this fits with other research
Moeyaert et al. (2016) looked at four older programs and said WebPlotDigitizer and Ungraph were the best picks. They did not test PlotDigitizer.
Aydin et al. (2022) now fill that gap. They show PlotDigitizer works just as well, and it costs nothing.
Together, the two papers give you a short shopping list: use WebPlotDigitizer or PlotDigitizer when you need free, accurate extraction.
Why it matters
If you meta-analyze single-case graphs, you no longer have to buy software. Download PlotDigitizer, run the quick validity checks shown in the paper, and start pulling data. It runs on Windows, Mac, or Linux, so every team member can use the same tool without license hassles.
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02At a glance
03Original abstract
Access to raw data of graphs presented in original articles to calculate the effect size of single-case research is a challenge for researchers conducting studies such as meta-analysis. Researchers typically use data extraction software programs to extract raw data from the graphs in articles. In this study, we aimed to analyze the validity and reliability of the PlotDigitizer software program, which is widely used in literature and an alternative to other data extraction programs, on computers with different operating systems. We performed the digitization of 6.846 data points on three different computers using 15 hypothetical graphs with 20 data series and 186 graphs with 242 data series from 29 published articles to accomplish the goal. Besides, using the values we digitized, we recalculated the 23 effect sizes presented in the original articles for validity analysis. Based on our sampling, we calculated intercoder and intracoder Pearson correlation coefficients. The results showed that PlotDigitizer could be an alternative to other programs as it is free and can run on many current and outdated systems, and it is valid and reliable as it is nearly perfect. Based on the obtained results and considering the data extraction process, we presented various recommendations for the researchers that will use the PlotDigitizer program for the quantitative analysis of single-case graphs.
Perspectives on Behavior Science, 2022 · doi:10.1007/s40614-021-00284-0