Hierarchical and Mixed Effects Models in R

Starting at USD 39.00
4 hours duration

In this course you will learn to fit hierarchical models with random effects.

This course provides a comprehensive overview of linear regression techniques, starting with a review of slopes and intercepts. It then progresses to the concept of random-effects and how they can be utilized to effectively model data. Moving forward, the course delves into the realm of linear mixed-effect regressions, which offer a powerful approach to analyzing data with complex structures beyond what standard linear regression can handle. Furthermore, the course covers generalized linear mixed-effect regressions, which enable the modeling of various types of data, including binary responses and count data. Lastly, the course explores repeated-measures analysis as a specialized application of mixed-effect modeling. This type of analysis is particularly relevant when studying subjects over time and collecting measurements at regular intervals. Throughout the course, you will have the opportunity to work with real-world data, allowing you to apply mixed-effects models to address intriguing research questions.

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Online Education Provider ยท 410 courses
DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.
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