綜合驗證性因素分析標記變數法在體能自我意識情緒量表中的應用

Application of Integrated Confirmatory Factor Analysis Marker Variable Method on Body-Related Self-Conscious Emotions Fitness Instrument

蘇榮海(Rong-Hai Su) ； 蘇冰心(Bing-Xin Su) ； 徐茂洲(Mao-Chou Hsu)

《大專體育》 159期 (2021/12) Pp. 25-43

https://doi.org/10.6162/SRR.202112_(159).0002

摘要

本研究目的以納入新科技樂觀性標記變數的體能自我意識情緒量表為研究工具，梳理了綜合驗證性因素分析（confirmatory factor analysis, CFA）標記變數法的提出過程，解釋了綜合CFA標記變數法的操作步驟，以舉例形式利用綜合CFA標記變數法檢驗了共同方法變異（common method variance, CMV），綜合CFA標記變數法在未來研究中能得到更好地推廣與應用。研究結果顯示：五模型比較結果表明，方法構念對既有構念之間的關係沒有顯著影響，方法構念不會造成偏誤，表示即使有CMV的存在，也不會影響模型估計的參數。因此，模型無需做CMV校正，表明研究資料無CMV問題。信度分析結果表明，構念因素變異數為0.61，方法因素變異數為0.02。進一步支持了CMV對本文報告的結果沒有顯著威脅。敏感度分析結果表明，方法構念中各觀察變數的信賴區間均符合標準，可以推斷抽樣誤差對CMV的潛在影響可以忽略不計。本研究結論：即便綜合CFA標記變數法有獨立觀察、樣本數、多元常態和連續型資料、選擇理想標記變數等限制，但其彌補了以往諸如Harman的單因素檢驗、多特質─多方法模型等CMV統計控制方法的諸多缺陷，考慮了CMV對指標變數影響的一致性，並根據Δχ^2差異直接比對模型優劣，在理論層面更優越、更嚴謹，在未來研究中仍然值得推廣和借鑒。

關鍵字

共同方法變異 ； 方法構念 ； Harman的單因素檢驗 ； 多特質─多方法模型

並列摘要

The purpose of this study was to take the Body-related Self-Conscious Emotions Fitness Instrument, which incorporates a new set of technology optimism marker variables as a research tool, to sort out the proposal process for the integrated confirmatory factor analysis (CFA) marker variable method and explain its operational steps. As an illustrative case, the common method variance was tested using the integrated CFA marker variable method. Results of a five-model comparison indicated that method constructs have no significant effect on the relationship between existing constructs and will not cause bias, indicating that the parameters estimated by the model will not be affected even in the case of common method variance (CMV). Therefore, no CMV issues exist in the research data, and CMV correction of the model is not necessary. In addition, reliability analysis results show that the variance of constructive factors is 0.61 and the variance of method factors is 0.02, lending further support to the argument that CMV poses no significant threat to the results. With reference to the sensitivity analysis results, the confidence interval of each observation variable in the method construct meets the standard; it can be inferred that the potential impact of sampling error on CMV is negligible. In conclusion: Limitations of the integrated CFA marker variable method include independent observation, number of samples, multiple normal and continuous data as well as selection of ideal marker variables. However, these limitations should be balanced against the many shortcomings of previous CMV statistical control methods such as Harman's single factor test and the multi-trait multi-method mode. Many shortcomings of CMV statistical control methods are unmeasured, such as latent method constructs. Considering the consistency of the influence of CMV on index variables, and directly comparing the pros and cons of the models according to the difference of Δχ^2, the integrated CFA marker variable method is superior and more rigorous in theory. It is still worthy of promotion and reference.

並列關鍵字

common method variance ； method construct ； Harman's single factor test ； multi-trait multi-method model

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