H as a measure of complexity of social information processing
H as a measure of complexity of social information processing
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DOI：
10.1207/s15327957pspr0703_05
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发表时间：
2003-01-01
影响因子：
10.8
通讯作者：
Locke, KD
中科院分区：
文献类型：
--
作者：
Locke, KD
许多研究使用 H（源自信息论的不可预测性度量）来量化跨多个角色的人员描述的复杂性。然而，解释这些研究是有问题的，因为 H 混淆了角色之间的不可预测性（这通常是兴趣的构建）和角色内的不可预测性（这只是认可特征比例的函数）。 3 项示范研究强调了控制角色内部不可预测性的必要性，其中控制角色内部的不可预测性消除了幸福感与 H 之间的关系。我还展示了如何控制由于认可的特征数量和描述的角色数量而导致的不可预测性，H 提供了一种独特的角色依赖性和独立性衡量标准。然而，H. 并没有测量可以预测角色之间“溢出效应”的角色类型。因此，我建议为未来的溢出效应研究使用一个替代的角色相似性指数。
Many studies have used H (a measure of unpredictability derived from information theory) to quantify the complexity of descriptions of persons across multiple roles. Interpreting these studies is problematic, though, because H confounds unpredictability across roles (which is typically the construct of interest) and unpredictability within roles (which is simply a function of the proportion of traits endorsed). The need to control for unpredictability within roles was highlighted by 3 demonstration studies in which controlling for unpredictability within roles eliminated relations between well-being and H. I also show how, controlling for unpredictability due to the number of traits endorsed and number of roles described, H provides a unique measure of role dependence and independence. However, H. does not measure the type of role over laps that would predict "spillover effects" between roles; therefore, I recommend an alternative index of role similarity for future research on spillover effects.