英文摘要
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Background: The methodology of mediation is commonly used in social science, health, psychological, educational, and sociological research (Wu & Zumbo, 2008). Unfortunately, mediation effects have been widely misunderstood and misused as data analytical tools and statistical hypothesis testing with little theoretical and methodological considerations. (Frazier, Tix, & Baron, 2004; MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002). Aims: The current paper aims to clarify the concept of mediation and investigate data analytical strategies for testing mediation effects. Hopefully, the results could assist researchers in designing and conducting their studies when mediation effects are examined. Discussion focus: In addition to clarifying the concept of mediation, this paper compares three analytical approaches for testing mediation effects, namely, Kenny’s causal steps analysis, Sobel test, and bootstrap procedure. Besides data analyzing procedures, strengths and weaknesses of these methods are discussed. Conclusion: These data analytical methods all have their limitations. Researchers should use them with caution. An integrated strategy is suggested when mediation effects are tested. By examining the testing results obtained from each approach simultaneously, it is more likely to gain a valid result.
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