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Multilevel Modeling: Analyze Hierarchical Data with R

Master multilevel modeling techniques for analyzing nested data structures using R programming in this intermediate-level course.

Master multilevel modeling techniques for analyzing nested data structures using R programming in this intermediate-level course.

This course provides an in-depth introduction to multilevel modeling, focusing on two-level models with continuous response variables. Designed for PhD candidates and researchers, it covers both the theoretical foundations and practical applications of multilevel analysis using R programming. The curriculum addresses the challenges of analyzing hierarchical data, where observations are nested within higher-level units (e.g., students within schools or repeated measures within individuals). Participants will learn why traditional statistical methods fall short for such data structures and how multilevel modeling overcomes these limitations. The course progresses from basic concepts to more advanced topics, including random slopes, cross-level interactions, and methodological considerations like centering. Through a combination of video lectures, quizzes, and hands-on R exercises, learners will develop the skills to conduct and interpret multilevel analyses. By the end of the course, participants will be equipped to apply multilevel modeling techniques to their own research, handling complex data structures and accounting for both individual and contextual effects in their analyses.

3.9

(15 ratings)

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Multilevel Modeling: Analyze Hierarchical Data with R

This course includes

7 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

2,436

What you'll learn

  • Understand the theoretical foundations of multilevel modeling

  • Build and interpret basic two-level multilevel models

  • Implement multilevel regression analyses using R programming

  • Develop models with random slopes and cross-level interactions

  • Apply appropriate centering techniques in multilevel analyses

  • Interpret and report results from multilevel models

Skills you'll gain

Multilevel regression
R programming
Hierarchical data analysis
Random slopes
Cross-level interactions
Data centering
Statistical modeling

This course includes:

105 Minutes PreRecorded video

3 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

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There are 4 modules in this course

This course offers a comprehensive introduction to multilevel modeling, a powerful statistical technique for analyzing hierarchical data structures. It begins by explaining the need for multilevel analysis and its advantages over traditional regression methods when dealing with nested data. The curriculum then progresses through the fundamentals of building and interpreting multilevel models, starting with basic two-level models and advancing to more complex structures with random slopes and cross-level interactions. Throughout the course, theoretical concepts are paired with practical applications using R programming, ensuring that participants gain both conceptual understanding and hands-on skills. Key topics include the steps of conducting a multilevel analysis, methodological considerations such as centering and aggregation, and interpreting model results. The course emphasizes real-world applications, providing learners with the tools to apply multilevel modeling techniques to their own research projects. By the end of the program, participants will be well-equipped to handle complex data structures and account for both individual and contextual effects in their statistical analyses.

Errata

Module 1 · 10 Minutes to complete

Introduction to Multilevel Modeling (MLM)

Module 2 · 2 Hours to complete

Random Slopes and Cross-Level Interactions

Module 3 · 1 Hours to complete

Putting it all Together

Module 4 · 3 Hours to complete

Fee Structure

Payment options

Financial Aid

Instructor

Supporting Doctoral Education at Erasmus University Rotterdam

The Erasmus Graduate School of Social Sciences and the Humanities (EGSH) provides a robust training infrastructure and supportive environment for over 500 PhD candidates at Erasmus University Rotterdam. Established in September 2012, the EGSH is a collaborative initiative involving multiple faculties, including the Erasmus School of Social and Behavioural Sciences, the International Institute of Social Studies, and others. It aims to enhance research talent by offering access to courses, workshops, and various support services tailored to doctoral students across ten academic fields. Through its commitment to fostering academic excellence and interdisciplinary collaboration, the EGSH plays a crucial role in advancing social sciences and humanities research within the university.

Multilevel Modeling: Analyze Hierarchical Data with R

This course includes

7 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

2,436

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

3.9 course rating

15 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.