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중다기초선설계: 두 판 사이의 차이
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== 장점 == | == 장점 == | ||
중다기초선설계는 단일 대상에게 기초선(baseline) 측정 이후 중재를 시행하는 기존의 단일중재 설계에 비해 | 중다기초선설계는 단일 대상에게 기초선(baseline) 측정 이후 중재를 시행하는 기존의 단일중재 설계에 비해 장점을 가지고 있다. 각 연구대상마다 시차를 두고 처치(treatment)를 시작하기 때문에, 각 연구대상마다 중재에 따라서 동일한 결과가 나왔다면, 처치에 따른 결과가 우연적이지 않았음을 확인할 수 있다. | ||
By gathering data from many subjects (instances), inferences can be made about the likeliness that the measured trait generalizes to a greater population. In multiple baseline designs, 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 baseline has been recorded, and does not finish until measures regain stability.[1] If a significant change occurs across all participants the experimenter may infer that the treatment is effective. | |||
Multiple base-line 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. Multiple baseline designs 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 base-line 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. Multiple baseline designs 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. | ||