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Diverse pathways to positive and negative affect in adulthood and later life: An integrative approach using recursive partitioning

机译:成年和以后生活中获得正面和负面影响的不同途径:使用递归划分的综合方法

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Recursive partitioning is an analytic technique that is useful for identifying complex combinations of conditions that predict particular outcomes as well as for delineating multiple subgroup differences in how such factors work together. As such, the methodology is welt suited to multidisciplinary, life course inquiry in which the goal is to integrate many interacting influences and understand subgroup variation. The authors conducted recursive partitioning analyses on a previously published study (D. K. Mroczek & C. M. Kolarz, 1998) that investigated life course profiles of positive and negative affect and incorporated various top-down (personality traits) and bottom-up (sociodemographic statuses, contextual influences) influences. The new analyses reveal multiway, nonlinear interactions among these variables in predicting affective experience and, importantly, life course differences in how these various factors combine. Included are details of how recursive partitioning trees are generated as well as descriptions of the software packages available for using such techniques. Overall, the methodology offers tractable strategies for discerning meaningful patterns in highly complex data sets.
机译:递归分区是一种分析技术,可用于识别预测特定结果的复杂条件组合,以及描述这些因素如何共同作用的多个亚组差异。因此,该方法适用于多学科的生命历程探索,其目标是整合许多相互作用的影响并了解亚组变异。作者在先前发表的研究(DK Mroczek&CM Kolarz,1998)中进行了递归划分分析,该研究调查了正面和负面影响的人生历程概况,并纳入了各种自上而下(人格特质)和自下而上(社会电生理状态,情境影响) )的影响。新的分析揭示了在预测情感体验时这些变量之间的多重非线性交互作用,而且重要的是,在这些因素的组合中生活过程的差异。其中包括有关如何生成递归分区树的详细信息,以及可用于使用此类技术的软件包的说明。总体而言,该方法提供了易于处理的策略,可用于识别高度复杂的数据集中的有意义的模式。

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