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Barsha Saha
In this project, you will learn to perform mediation analysis in RStudio. The project explains the theoretical concepts of mediation and illustrates the process with sample stress detection data. It covers the distinction between mediation and moderation...
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In this project, you will learn to perform mediation analysis in RStudio. The project explains the theoretical concepts of mediation and illustrates the process with sample stress detection data. It covers the distinction between mediation and moderation process, explains the selection criteria for a suitable mediator. The project describes the mediation process with statistical models, diagnostic measures and conceptual diagram.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Appropriate for research scholars who want to leverage RStudio for mediation analysis
Covers theoretical and practical aspects of mediation analysis in a structured manner
Provides hands-on experience with sample data for immediate application of concepts
Requires basic knowledge of statistical concepts and RStudio
Suitable for students and researchers involved in data analysis and interpretation
Provides a strong foundation for understanding and conducting mediation analysis

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Mediation Analysis with R with these activities:
Practice selecting appropriate mediators
Enhance your understanding of criteria for selecting mediators and practice applying them to different scenarios.
Show steps
  • Review the criteria for selecting a mediator
  • Analyze different datasets
  • Identify potential mediators
  • Evaluate the suitability of each mediator
Practice writing mediation models in R
Focus on understanding mediation model syntax and applying it to real-world datasets to improve your comprehension.
Show steps
  • Review the theoretical concepts of mediation
  • Install RStudio and the required packages
  • Load the sample stress detection data
  • Write a mediation model in RStudio
  • Interpret the results and draw conclusions
Explore mediation analysis tutorials
Supplement your learning by exploring external tutorials that provide step-by-step guidance and additional examples.
Show steps
  • Identify reputable online tutorials
  • Follow the tutorials and work through the examples
  • Apply what you learn to your own datasets
Show all three activities

Career center

Learners who complete Mediation Analysis with R will develop knowledge and skills that may be useful to these careers:
Statistician
A Statistician collects, analyzes, and interprets data to provide insights and make predictions. They play a crucial role in various industries, from healthcare to finance. This course can help you enhance your statistical skills, particularly in mediation analysis. By mastering mediation analysis, you can make more accurate predictions and provide more valuable insights.
Quantitative Researcher
A Quantitative Researcher uses statistical methods to analyze data and solve problems. They work in various fields, such as finance, marketing, and healthcare. This course can help you develop the skills necessary to perform mediation analysis, enabling you to make more informed decisions and contribute to better outcomes.
Survey Researcher
A Survey Researcher designs, conducts, and analyzes surveys to collect data on a specific topic. They work in market research, public opinion polling, and social science research. This course can provide you with a foundation in statistical modeling, including mediation analysis. By understanding mediation, you can design more effective surveys and analyze data more accurately.
Biostatistician
A Biostatistician applies statistical methods to solve problems in biology and medicine. They work in academia, industry, and government agencies. This course can help you develop the skills necessary to perform mediation analysis, enabling you to make more informed decisions and contribute to better patient outcomes.
Data Scientist
A Data Scientist analyzes data to extract meaningful insights and patterns. They help businesses make better decisions based on data-driven evidence. This course can help you gain the skills needed to perform mediation analysis, a statistical technique used to identify the causal relationships between variables. By understanding mediation, you can become a more effective Data Scientist and contribute to more informed decision-making.
Market Researcher
A Market Researcher gathers and analyzes data to understand consumer behavior and market trends. They work in various industries, including marketing, advertising, and product development. This course can help you develop the skills necessary to perform mediation analysis, enabling you to make more informed decisions and develop more effective marketing strategies.
Epidemiologist
An Epidemiologist investigates the distribution and determinants of health-related states or events in a population. They work in public health, healthcare, and research institutions. This course can provide you with a solid understanding of statistical modeling, including mediation analysis. By understanding mediation, you can better understand the causal relationships between different factors and health outcomes.
Operations Research Analyst
An Operations Research Analyst uses mathematical and statistical methods to improve the efficiency and effectiveness of organizations. They work in a variety of industries, including manufacturing, transportation, and healthcare. This course can provide you with a foundation in statistical modeling, including mediation analysis. By understanding mediation, you can make more informed decisions and contribute to better decision-making across the organization.
Data Analyst
A Data Analyst collects, cleans, and analyzes data to extract meaningful insights. They work in various industries, including finance, healthcare, and technology. This course can provide you with a foundation in statistical modeling, including mediation analysis. By understanding mediation, you can make more informed decisions and contribute to better data-driven outcomes.
Public Health Analyst
A Public Health Analyst collects and analyzes data to identify and address public health issues. They work in local, state, and federal government agencies. This course can provide you with a foundation in statistical modeling, including mediation analysis. By understanding mediation, you can make more informed recommendations for public health policy and interventions.
Healthcare Analyst
A Healthcare Analyst collects and analyzes data to improve the quality and efficiency of healthcare delivery. They work in hospitals, clinics, and other healthcare organizations. This course can provide you with a foundation in statistical modeling, including mediation analysis. By understanding mediation, you can make more informed decisions about healthcare policy and interventions.
Actuary
An Actuary assesses financial risks and develops strategies to mitigate them. They work in insurance, consulting, and other financial sectors. This course can help you build a foundation in statistical modeling, including mediation analysis. By understanding mediation, you can make more informed decisions about financial risks and develop more effective risk management strategies.
Business Analyst
A Business Analyst analyzes business processes and systems to identify inefficiencies and opportunities for improvement. They work in various industries, including finance, healthcare, and technology. This course can provide you with a foundation in statistical modeling, including mediation analysis. By understanding mediation, you can make more informed recommendations for business process improvement.
Social Scientist
A Social Scientist studies human behavior and social patterns. They work in academia, government agencies, and non-profit organizations. This course can provide you with a foundation in statistical modeling, including mediation analysis. By understanding mediation, you can better understand the causal relationships between different factors and social outcomes.
Machine Learning Engineer
A Machine Learning Engineer builds and maintains machine learning models to solve complex problems. They work in industries such as technology, finance, and healthcare. This course can provide you with a solid foundation in statistical modeling, including mediation analysis. By understanding mediation, you can improve the accuracy and interpretability of your machine learning models.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Mediation Analysis with R.
Provides a comprehensive overview of advanced statistical methods, including mediation analysis. It would be useful for those who want to learn more about this topic, or for those who are specifically interested in using advanced statistical methods in mediation analysis.
Provides a comprehensive overview of applied Bayesian hierarchical methods. It would be useful for those who want to learn more about this topic, or for those who are specifically interested in using Bayesian methods in mediation analysis.
Provides a comprehensive overview of mediation analysis. It covers the theoretical foundations of mediation, the different types of mediation models, and the statistical methods used to test for mediation.
Covers structural equation modeling (SEM), which more advanced statistical technique that can be used to test mediation models. It would be useful for those who want to learn more about SEM or for those who are looking for a more in-depth treatment of mediation analysis.
Provides a comprehensive overview of the analysis of ordinal categorical data. It would be useful for those who want to learn more about this topic, or for those who are specifically interested in mediation analysis of ordinal categorical data.
Provides a step-by-step guide to mediation, moderation, and conditional process analysis using a regression-based approach. It is written in a clear and concise style and is suitable for readers with a basic understanding of statistics.
Provides a comprehensive overview of mediation and moderation analysis. It covers the theoretical foundations of mediation and moderation, the different types of mediation and moderation models, and the statistical methods used to test for mediation and moderation.
Provides a comprehensive overview of nonparametric statistical methods. It would be useful for those who want to learn more about this topic, or for those who are specifically interested in using nonparametric methods in mediation analysis.
Focuses on mediation analysis in the context of communication research. It would be particularly useful for those who are interested in using mediation analysis to study communication processes.

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