Interrupted time-series analysis and its application to behavioral data.

Hartmann et al. (1980) wrote a how-to guide. They explain interrupted time-series analysis, or ITSA.

ITSA is a math tool for single-case graphs. It checks if a treatment really changed the line.

The paper is pure method. No kids, no trials, just stats.

The authors show step-by-step formulas. You plug in your daily behavior counts.

The math gives you a p-value and a confidence band. It tells if the slope or level shifted after you started treatment.

Falligant et al. (2020) and Tassé et al. (2013) both used single-case designs. Their graphs of stereotypy data are perfect for ITSA.

Hawkes et al. (1974) ran an A-B-A-B study. The target paper’s formulas could test the play-skill jumps seen in that 1974 data.

Hsieh et al. (2011) tracked parent fidelity across days. ITSA could replace eye-ball judgment of those trend lines.

You no longer have to trust your eyes alone. Run ITSA on your next single-case graph. It takes five minutes in free software. You get a clear number to show parents, teachers, or insurance reviewers that the change is real.