Learn how to specify, fit, interpret, evaluate and compare estimated parameters with linear mixed-effects models in R.
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Specify an appropriate linear mixed-effects model structure with their own data.
Compare alternative modeling structures and choose the best specification.
Represent, fit, and choose among different, competing correlational structures appropriate to both temporal and spatial pseudo-replicated models.
Validate the "goodness" of the model and the model assumptions.
Represent, estimate, interpret and report on linear mixed-effects model parameters using R software.
This comprehensive Linear Mixed-Effects Models with R curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
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What you need before starting this Linear Mixed-Effects Models with R course:
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Everything you need to know about this online course, from duration to certification
Course Instructor
Geoffrey Hubona, Ph.D.
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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