Results of single-case research designs (i.e., n-of-1 trials) are often evaluated by visually inspecting the time-series graph and computing quantitative indices. A question our research team is pondering is whether visual analysis or quantitative indices should be set as the criterion for determining effects from experiments. I'd appreciate thoughts from both sides of the argument.
I once heard visual analysis as referred to as an "inter-ocular traumatization test" -- did the results hit you between the eyes? the problem is that one person's noteworthy dip or spike is another's blip in the data. But since you are working in a team, you could each independently mark what you consider to be the major change points and then determine how much consensus you have.
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