政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/141635

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/141635

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政大典藏 > College of Science > Department of Psychology > Theses > Item 140.119/141635

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/141635

Title:	非重疊型指標作為量化單一受試者實驗設計介入效果之強韌性研究 The Robustness of Nonoverlap Indices as Effect Size Measures in Single Case Experimental Design: A Simulation Study
Authors:	黃任清 Huang, Jen-Ching
Contributors:	游琇婷 Yu, Hsiu-Ting 黃任清 Huang, Jen-Ching
Keywords:	單一個案研究非重疊型指標效果量指標時間序列資料 Single-case research Nonoverlap indices Effect size Time series data
Date:	2022
Issue Date:	2022-09-02 15:04:09 (UTC+8)
Abstract:	在臨床心理學和特殊教育領域常使用單一受試者實驗設計進行研究。此研究法比較個案的目標行為於介入前後的差異以評估介入方案的效果。單一受試者實驗設計可用目視分析評量介入方案是否有效，但需要客觀的量化分析指標以進行跨受試者的比較。量化分析方法中的非重疊型效果量指標計算基線期與介入期間資料的不重疊比例，可作為介入效果的效果量指標。非重疊型指標計算簡單、解釋直觀且對依變項分配並無假設，然而卻可能受到時間序列資料等資料特徵的影響而產生偏誤。可能影響指標的資料特徵包含序列相依性、序列長度、趨勢、資料變異程度以及效果即刻性。本研究以模擬研究操弄資料特徵之型態與強度，比較十種非重疊型指標（ECL、PND、PAND、 PEM、PNCD、IRD、 NAP、Tau、Tau-U 以及基線期校正 Tau）估計介入效果時受資料特徵影響的程度及強韌性。研究發現NAP、Tau、和 Tau-U 能避免受到序列相依性的影響；NAP 和 Tau 對序列長度有最好的強韌性；PNCD 和基線期校正 Tau 於資料中有直線趨勢時有最好的強韌性，而 Tau-U則可應用於各類趨勢型態；PEM 可以避免變異程度的影響；PND 對效果未即刻顯現時有最好的強韌性。本研究建議應依照資料特性選擇適切的非重疊型指標以估計單一受試者實驗設計的介入效果。 Single-case experimental design (SCED) commonly applies to clinical psychology and special education research for examining the treatment effect of an intervention. The typical approach is comparing the changes in target behavior of participant before and after an intervention. While visual analysis can be easily used to assess intervention effect, quantitative methods are required for cross-subject comparisons. The nonoverlap effect size measures are one of the SCED objective indices which evaluate the percentage of nonoverlapping data between baseline and intervention phases. Nonoverlap indices are easy to calculate and intuitive to interpret, and they can be applied without making assumptions about the distributions of dependent variables. However, data features of repeated measurements may impact the accuracy of nonoverlap indices in quantifying the treatment effect. Common data features in SCED are serial dependence, series length, trend, variability, and immediacy of effect. A series of simulation studies were conducted to assess the performance of nonoverlap indices for data sets with difference data features. Performance of ten nonoverlap indices (ECL, PND, PAND, PEM, PNCD, IRD, NAP, Tau, Tau-U and baseline corrected Tau) were compared and evaluated the robustness of these indices. Research results suggested NAP, Tau and Tau-U perform well under data sets with serial dependence; The two indices, NAP and Tau, were robust under difference series lengths; PNCD and baseline corrected Tau are suitable for data with linear trend; Tau-U can be applied to data with various trend types; PEM is the least among the compared indices affected by the data variability; and PND is the most robust effect size measure when the effect is not exhibited immediately after the intervention. We suggest SCED researchers to select appropriate nonoverlap indices on the bases of data features to quantify the intervention effect of their study accurately.
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Description:	碩士國立政治大學心理學系 106752003
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0106752003
Data Type:	thesis
DOI:	10.6814/NCCU202201209
Appears in Collections:	[Department of Psychology] Theses

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