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所在平台: Udemy |
课程主页: https://www.udemy.com/course/multivariate-da-in-r-for-research-scholars-advance/
课程评论：没有评论
**Coursera课程：R语言中的多元数据分析** 本课程专为研究学者设计，旨在教授R语言中的多元统计技术，包括结构方程模型（SEM）、验证性因子分析（CFA）和探索性因子分析（EFA），以及逻辑回归。 **课程亮点：** * **结构方程模型（SEM）：** 深入讲解如何在R中实现SEM，特别是高阶结构模型和中介效应（包含潜变量），并清晰解释SEM作为CFA和线性回归的结合。课程将复杂的高阶建模和中介/调节方法简化讲解。 * **验证性因子分析（CFA）：** 涵盖CFA的基本概念和术语，以及如何通过CFA来验证问卷，包括复合信度（Composite Reliability）、判别效度（Discriminant Validity）和平均方差提取（Average Variance Extracted）等指标。课程会解释数学公式，帮助理解因子与观测变量之间的关系。 * **探索性因子分析（EFA）：** 侧重于在研究报告和论文中如何执行EFA并解释结果。课程讲解所有必要的先决条件，并且所有教学都基于研究者已通过问卷收集了原始数据。 * **逻辑回归（Logistic Regression）：** 包含从基本概念到模型实现、结果解释以及模型有效性检验的全面讲解，这是一项监督式机器学习技术。 **课程特点：** * **实用导向：** 课程以研究者的实际需求为出发点，尤其关注如何在研究报告或论文中应用和呈现这些分析方法。 * **R语言实现：** 所有技术均使用R语言中的`lavaan`包进行实现。 * **易于理解：** 尽管视频没有涵盖所有统计术语的深入细节，但提供了足够的研究者在撰写论文时所需的知识和理解。 **目标学员：** * 需要使用SEM、EFA和CFA进行数据分析的研究学者。 * 希望在R语言中实现这些分析的研究导师。 * 对逻辑回归技术感兴趣的学习者。 本课程将帮助您解锁数据的奥秘，掌握强大的多元数据分析工具。
Unlock and Explore the Secrets of Data: Master multivariate Statistical Techniques and Logistic Regression. The course contains detailed videos on following1) How to implement Structural Equation Modeling (SEM) more importantly including higher order constructs and mediation with latent variables. Basically, SEM is a combination of CFA and Linear Regression. Creation of Higher order (or hierarchical component models) has an inherited complexity which is also compounded by mediation/moderation methods. Still I have tried to keep it as simple as possible.2) Implementing confirmatory factor analysis (CFA), explanation of basic concepts and terms in CFA and how to validate questionnaire through CFA including metrics like Composite Reliability, Discriminant validity and Average variance extracted. The mathematical equations are also explained to a level, which help in understanding the relation between Factors and Observed variables and various other terms used in CFA.3) Executing EFA and interpreting the results from the point of view of documenting in Research Reports/ Thesis. All the prerequisites have been explained too. All the sessions start from where the scholar has collected the primary data through a questionnaire.The lectures may not have in depth details of all statistical terms, nevertheless, they provide sufficient awareness, which can help researchers document their thesis.Lavaan library has been used in R Studio for implementation of all the above methodsAgain, if you are looking on implementation SEM, EFA and CFA in R, with a point of view of research scholar or research supervisor, this is exactly for you.Additionally, This course also contains lectures on Logistic Regression (supervised machine learning technique), from the basic concepts to its implementation to interpretation of results and checking effectiveness of LR model.
