The good, the bad, and the aggregate.

Geckeler et al. (2000) wrote a think-piece, not an experiment. They asked: is it okay for behavior analysts to add up results from many single-subject studies?

The authors say yes. They argue that counting and averaging findings is the only way to see which behavior laws hold across people, places, and times.

The paper finds no new data. Instead it gives a road map: gather studies, extract numbers, look for patterns, and still keep single-subject values in view.

They claim this blend keeps the soul of behavior analysis while borrowing the muscle of meta-analysis.

Reid et al. (1999) made the same point one year earlier. Both papers defend adding single-subject data, but the 1999 team warns: call it "quantitative integration," not meta-analysis. Geckeler et al. (2000) widen the plea to any kind of literature review.

Slaton et al. (2018) later showed the idea in action. Their review lumped together 80 functional-analysis studies that used synthesized conditions. The paper proves behavior analysts already pool data when it helps.

Halstead (2002) went further and counted every citation in ABA journals. That bibliometric study is a live example of the 2000 paper’s call: add up the evidence to see the field’s true shape.

If you stick to one-client graphs alone, you may miss big trends. Try a quick count in your next literature search: tally how often a procedure works across the last ten studies. That tiny step is quantitative synthesis, and this paper says it is allowed.