Linear Trend in Single-Case Visual and Quantitative Analyses.
Use the free WWC web app to compare slopes, not detrending, when you judge trend change in single-case data.
01Research in Context
What this study did
Manolov (2018) wrote a how-to paper on spotting straight-line trends in single-case graphs. The author built a free web app that follows the What Works Clearinghouse rules.
You paste in your data. The tool draws the graph and checks if the slope really changed after the intervention.
What they found
The paper says: skip the old detrending step. Just compare the slope before and after the phase line.
The web app gives you the numbers in seconds. No spreadsheets. No formulas.
How this fits with other research
Solanas et al. (2010) told us to detrend first, then look at level change. Manolov (2018) now says detrending adds noise—compare slopes instead. The new method replaces the old one.
Tyrer et al. (2006) warned that stats and eyes can disagree. Rumen keeps the visual check but adds a WWC-aligned number so you get both.
Manolov (2026) and Manolov et al. (2022) later built more free web tools for wider SCED jobs. They extend the same idea: good analysis should be one click away.
Why it matters
Next time you stare at an AB graph and wonder if the trend really moved, open the free WWC app. Paste your data. Read the slope numbers. If they jump, you have quick, reviewer-friendly evidence. No stats degree needed.
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02At a glance
03Original abstract
The frequently used visual analysis of single-case data focuses on data aspects such as level, trend, variability, overlap, immediacy of effect, and consistency of data patterns; most of these aspects are also commonly quantified besides inspecting them visually. The present text focuses on trend, because even linear trend can be operatively defined in several different ways, while there are also different approaches for controlling for baseline trend. We recommend using a quantitative criterion for choosing a trend line fitting technique and comparing baseline and intervention slopes, instead of detrending. We implement our proposal in a free web-based application created specifically for following the What Works Clearinghouse Standards recommendations for visual analysis. This application is especially destined to applied researchers and provides graphical representation of the data, visual aids, and quantifications of the difference between phases in terms of level, trend, and overlap, as well as two quantifications of the immediate effect. An evaluation of the consistency of effects across replications of the AB sequence is also provided. For methodologists and statisticians, we include formulas and examples of the different straight line fitting and detrending techniques to improve the reproducibility of results and simulations.
Behavior modification, 2018 · doi:10.1177/0145445517726301