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A Bifactor Approach to Subscore Assessment

机译：子分数评估的双因素方法

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Translational Abstract Statistical indices within the bifactor confirmatory factor analytic framework have previously been developed to aid researchers about the acceptability of treating multidimensional data as essentially unidimensional for interpretation purposes. However, despite the utility of bifactor indices, it is unknown if bifactor indices can aid applied researchers wanting to know if subscores can be interpreted with confidence in the presence of a bifactor solution. In this experimental simulation study we evaluated the utility of bifactor indices and provide recommendations around when researchers may consider a subscore as having added value beyond a total score interpretation when such an interpretation is desired. Specifically, cutoffs were devised for a specific factor's bifactor indices OmegaHS and ECVSS, conditioned upon OmegaS and number of specific factors, such that exceeding these cutoffs indicates the subscore has added value over the total score. Second, we illustrate the use of these cutoffs with an empirical data set along with practical interpretations of the bifactor indices. Overall, the current research provides results that aid psychology, education and, more generally, social science researchers in making rigorous decisions about whether to interpret subscores for use in research and in practical settings. Bifactor confirmatory factor analysis models and statistical indices computed from them have previously been used to provide evidence for the appropriateness of utilizing a unidimensional interpretation of multidimensional data. However, the ability of bifactor indices to aid in the assessment of subscore strength has not been investigated. A simulation study was conducted to relate bifactor indices to the strength of subscores corresponding to specific factors. The bifactor indices OmegaHS and ECVSS were found to be strongly predictive of subscore strength conditional upon OmegaS. The number of factors was also found to play a minor role in this relationship. Cutoffs for assessing the appropriateness of interpreting subscores were constructed based on OmegaHS or ECVSS conditional upon OmegaS and the number of factors. For low subscore reliability (OmegaS = .60), OmegaHS = .25 or ECVSS = .45 is sufficient that the subscore has a good chance of having added value (VAR > 1.1) above and beyond the total score. For moderate reliability (OmegaS = .80), OmegaHS = .20 or ECVSS = .30 is sufficient, and the role of OmegaHS or ECVSS diminishes as OmegaS increases further. A subscore having added value does not necessitate its interpretation. Instead, when subscores are desired to be interpreted, high OmegaHS or ECVSS can be considered as evidence that such an interpretation is statistically appropriate. Finally, we illustrate the use of these cutoffs with an empirical data set. When combined with prior bifactor research, this work extends a framework of using confirmatory bifactor models for dimensionality assessment.
机译：转化抽象的统计指标bifactor验证性因素分析框架以前开发援助研究人员对治疗的可接受性多维数据是一维的用于解释。然而,尽管bifactor指数的效用,如果bifactor指数可以帮助应用是未知的研究人员想知道如果部分的得分解释与信心的存在bifactor解决方案。我们评估工具的模拟研究bifactor指数和提供建议当研究人员可能会“考虑”的得分有附加价值超越了总分当这样的解释解释想要的。bifactor指数OmegaHS和特定的因素ECVSS,条件在欧米伽和数量等具体因素,超过这些切断“表示”的得分增加了价值总分。使用这些被切断与实证的数据集随着实际的解释bifactor指数。提供结果,援助心理学、教育更一般的,社会科学研究人员在严格的决策是否解释部分的得分在研究和使用实际设置。分析模型和统计指数计算从他们以前被用来提供利用适当的证据一维的多维的解释数据。在“评估”的得分实力的援助没有被调查。进行联系bifactor指数的部分的得分对应特定的力量的因素。被发现是“强烈预测”的得分强度条件在欧米茄。因素也扮演一个次要角色这种关系。适当的解释部分的得分构建基于OmegaHS或ECVSS条件欧米伽和数量的因素。subscore可靠性(ω= .60)OmegaHS =0。25或ECVSS =。45就足够了subscore有附加价值的一个好机会(VAR > 1.1)以外的总得分。温和的可靠性(ω= .80)OmegaHS =.20或ECVSS = .30是充分的,和的作用OmegaHS或ECVSS减少欧米伽增加进一步。需要解释。部分的得分的解释,高OmegaHS ECVSS也可以被认为是作为证据这样的解释是统计合适的。这些短裤与实证数据集。结合bifactor研究之前,这项工作扩展使用确认的一个框架bifactor维度评估模型。

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