Percentage of Non-Overlapping Data

First identify the single most extreme baseline point in the direction of desired change — the highest baseline value if you want the behavior to increase, the lowest if you want it to decrease. Then count how many intervention-phase points fall beyond that benchmark, divide by the total number of intervention points, and multiply by 100. The result is the percentage of the intervention phase that surpassed the best the baseline ever achieved, interpreted with bands where above 90 percent is very effective and below 50 percent is ineffective.

PND rests on a single extreme baseline point, so one outlying baseline observation can drag the index down regardless of how strong the intervention was. It also has a ceiling at 100 percent that cannot distinguish among very large effects, and it ignores trend in both phases, so an improving baseline can masquerade as an intervention effect or mask one. These weaknesses, documented over decades, are why researchers increasingly prefer trend-aware nonoverlap indices such as Tau-U, which Parker and colleagues introduced specifically to address them.

Several nonoverlap indices were developed to address PND's shortcomings, and Tau-U from Parker and colleagues in 2011 is the most prominent. Tau-U combines the nonoverlap between baseline and intervention phases with a correction for baseline trend, which makes it more robust to outliers, less affected by the ceiling, and able to account for slope that PND ignores. Other alternatives include the improvement rate difference and percentage of data exceeding the median. PND is still reported for continuity and simplicity, but trend-aware indices are now generally preferred.