Dyadic Multilevel Data Analysis in R
Friendly and detailed R Data Analysis guide, focusing on adequate and accurate advise.
The book titled 'Dyadic Multilevel Data Analysis in R' by Pascal Küng offers a friendly and detailed guide to R Data Analysis, focusing on providing adequate and accurate advice. It covers topics such as mixed effects modeling, model selection, and simplifying R output, making it a valuable resource for individuals interested in data analysis using R programming language.
How to use
To make the most of 'Dyadic Multilevel Data Analysis in R', follow these steps:
- Start by understanding the basics of R programming language.
- Read through the chapters sequentially for a comprehensive understanding.
- Apply the concepts discussed in each chapter on relevant datasets to practice and reinforce learning.
Features
- Comprehensive guide to Dyadic Multilevel Data Analysis in R
- Focus on mixed effects modeling and model selection
- Provides friendly and detailed advice on R Data Analysis
- Written by Pascal Küng
- Interactive prompts for engagement
Updates
2023/11/13
Language
English (English)
Welcome message
Hello! Let's explore R Data Analysis with clarity and friendliness!
Prompt starters
- How do I start with mixed effects modeling?
- Can you simplify this R output for me?
- What should I consider in model selection?
- Explain this statistical concept in simple terms, please.
Tools
- python
- dalle
- browser
Tags
public
reportable