• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Multivariate behavioral research >Modeling Interactions Between Latent Variables in Research on Type D Personality: A Monte Carlo Simulation and Clinical Study of Depression and Anxiety
【24h】

Modeling Interactions Between Latent Variables in Research on Type D Personality: A Monte Carlo Simulation and Clinical Study of Depression and Anxiety

机译：D型人格研究中潜在变量的建模相互作用：抑郁与焦虑的蒙特卡罗模拟与临床研究

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Several approaches exist to model interactions between latent variables. However, it is unclear how these perform when item scores are skewed and ordinal. Research on Type D personality serves as a good case study for that matter. In Study 1, we fitted a multivariate interaction model to predict depression and anxiety with Type D personality, operationalized as an interaction between its two subcomponents negative affectivity (NA) and social inhibition (SI). We constructed this interaction according to four approaches: (1) sum score product; (2) single product indicator; (3) matched product indicators; and (4) latent moderated structural equations (LMS). In Study 2, we compared these interaction models in a simulation study by assessing for each method the bias and precision of the estimated interaction effect under varying conditions. In Study 1, all methods showed a significant Type D effect on both depression and anxiety, although this effect diminished after including the NA and SI quadratic effects. Study 2 showed that the LMS approach performed best with respect to minimizing bias and maximizing power, even when item scores were ordinal and skewed. However, when latent traits were skewed LMS resulted in more false-positive conclusions, while the Matched PI approach adequately controlled the false-positive rate.
机译：存在几种方法来模拟潜在变量之间的相互作用。但是，目前尚不清楚当物品分数偏斜和序数时如何执行这些执行。 D型人格的研究是对此物质的一个很好的案例研究。在研究1中，我们拟合了多元相互作用模型，以预测D型人格的抑郁和焦虑，作为其两个子组件负面情感（NA）和社会抑制（SI）之间的相互作用。我们根据四种方法构建了这种互动：（1）总和分数产品; （2）单一产品指标; （3）匹配的产品指标; （4）潜在潜水结构方程（LMS）。在研究2中，我们通过评估各种方法在不同条件下进行估计的相互作用效果的偏差和精度来比较这些相互作用模型。在研究1中，所有方法都对抑郁和焦虑显示出显着的D型影响，尽管在包括NA和Si二次效应后这种效果减少。研究2表明，即使当物品分数序号并倾斜时，LMS方法也能够最小化偏差和最大化功率。然而，当潜在的性状偏斜LMS时，导致更虚假的结论，而匹配的PI方法充分控制了假阳性率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号