A<unk>  is used in medical, psychological, and biological research. The<unk>  was first reported in 1960 as used in basic operant research. It was applied in the late 1960s to human experiments in response to practical and ethical issues that arose in withdrawing apparently successful treatments from human subjects. In it two or more (often three) behaviors, people or settings are plotted in a staggered graph where a change is made to one, but not the other two, and then to the second, but not the third behavior, person or setting. Differential changes that occur to each behavior, person or in each setting help to strengthen what is essentially an AB<unk>  with its problematic competing hypotheses. Because treatment is started at different times, changes are attributable to the treatment rather than to a chance factor. By gathering data from many subjects (instances), inferences can be made about the likeliness that the measured trait generalizes to a greater population. In<unk> s, the experimenter starts by measuring a trait of interest, then applies a treatment before measuring that trait again. Treatment does not begin until a stable<unk>  has been recorded, and does not finish until measures regain stability. If a significant change occurs across all participants the experimenter may infer that the treatment is effective.<unk> <unk>  experiments are most commonly used in cases where the dependent variable is not expected to return to normal after the treatment has been applied, or when medical reasons forbid the withdrawal of a treatment. They often employ particular methods or recruiting participants.<unk> s are associated with potential confounds introduced by experimenter bias, which must be addressed to preserve objectivity. Particularly, researchers are advised to develop all test schedules and data collection limits beforehand.
Multiple baseline design
Solomon four-group design
N of 1 trial
Blinded experiment
Clinical study design
Parallel study
Natural history group
Natural history study