Research strategies in developmental psychopathology: Dimensional identity and the person-oriented approach
Research strategies in developmental psychopathology: Dimensional identity and the person-oriented approach
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DOI：
10.1017/s0954579403000294
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发表时间：
2003-06-01
影响因子：
3.3
通讯作者：
Bergman, LR
中科院分区：
文献类型：
--
作者：
Von Eye, A;Bergman, LR
本文讨论了发展精神病理学的其他研究策略。它认为统计方法在实证研究中的大多数应用是以变量为中心的，而不是以人为中心的。因此，得出的结论往往不能公正地对待人口的多样性。建议我们认真对待数据汇总的影响的重要性。从较集中的分析水平到较不集中的分析水平进行推论的困难被解释和举例说明。我们解释说，如果变量关系在其他变量的层次或类别中保持不变，则一组变量显示维度同一性。智力差异和儿童行为检查表亚群体差异的数据例子表明，缺乏维度认同可能导致不正确的结论。Schmitz关于聚合的定理和结果在个体的聚合水平上的有效性使用来自酗酒发展研究的数据来说明，并从个人导向的角度进行了讨论。统计方法适用于以人为本的数据分析进行了审查。
This article deals with alternative research strategies for developmental psychopathology. It argues that most applications of statistical methods in empirical research are variable centered, not person oriented. As a result, conclusions are often drawn that fail to do justice to the diverse nature of populations. It is recommended that we take seriously the importance of the implications of data aggregation. The difficulties of making inferences from a more aggregated level of analysis to a less aggregated level are explained and exemplified. We explain that a set of variables displays dimensional identity if the variable relationships remain unchanged across the levels or categories of other variables. Data examples of intelligence divergence and of Child Behavior Checklist subpopulation differences show that lack of dimensional identity can lead to incorrect conclusions. Schmitz' theorems on aggregation and the validity of results at the aggregate level for individuals are illustrated using data from a study on the development of alcoholism and discussed from a person-oriented perspective. Statistical methods suitable for person-oriented data analysis are reviewed.