利用社会关系结构方程模型分析纵向社会关系模型数据

IF 1.9 3区心理学 Q2 EDUCATION & EDUCATIONAL RESEARCH Journal of Educational and Behavioral Statistics Pub Date : 2021-12-14 DOI:10.3102/10769986211056541

S. Nestler, O. Lüdtke, A. Robitzsch

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引用次数: 4

摘要

社会关系模型（SRM）在心理学中经常用于研究社会群体中出现的人际判断和行为的组成部分、决定因素和后果。标准SRM是为分析横截面数据而开发的。基于最近提出的SRM与结构方程模型（SEM）框架的集成，我们在这里展示了如何使用SR-SEM分析纵向SRM数据。给出了两个例子来说明该模型，我们还给出了一个小型模拟研究的结果，将SR-SEM方法与两步方法进行了比较。总之，与早期分析纵向SRM数据的建议相比，SR-SEM具有许多优势，使其对应用研究非常有用。

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Analyzing Longitudinal Social Relations Model Data Using the Social Relations Structural Equation Model

The social relations model (SRM) is very often used in psychology to examine the components, determinants, and consequences of interpersonal judgments and behaviors that arise in social groups. The standard SRM was developed to analyze cross-sectional data. Based on a recently suggested integration of the SRM with structural equation models (SEM) framework, we show here how longitudinal SRM data can be analyzed using the SR-SEM. Two examples are presented to illustrate the model, and we also present the results of a small simulation study comparing the SR-SEM approach to a two-step approach. Altogether, the SR-SEM has a number of advantages compared to earlier suggestions for analyzing longitudinal SRM data, making it extremely useful for applied research.

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来源期刊

Journal of Educational and Behavioral Statistics Multiple-

CiteScore

4.40

自引率

4.20%

发文量

期刊介绍： Journal of Educational and Behavioral Statistics, sponsored jointly by the American Educational Research Association and the American Statistical Association, publishes articles that are original and provide methods that are useful to those studying problems and issues in educational or behavioral research. Typical papers introduce new methods of analysis. Critical reviews of current practice, tutorial presentations of less well known methods, and novel applications of already-known methods are also of interest. Papers discussing statistical techniques without specific educational or behavioral interest or focusing on substantive results without developing new statistical methods or models or making novel use of existing methods have lower priority. Simulation studies, either to demonstrate properties of an existing method or to compare several existing methods (without providing a new method), also have low priority. The Journal of Educational and Behavioral Statistics provides an outlet for papers that are original and provide methods that are useful to those studying problems and issues in educational or behavioral research. Typical papers introduce new methods of analysis, provide properties of these methods, and an example of use in education or behavioral research. Critical reviews of current practice, tutorial presentations of less well known methods, and novel applications of already-known methods are also sometimes accepted. Papers discussing statistical techniques without specific educational or behavioral interest or focusing on substantive results without developing new statistical methods or models or making novel use of existing methods have lower priority. Simulation studies, either to demonstrate properties of an existing method or to compare several existing methods (without providing a new method), also have low priority.