Multilevel Modeling from Coursera

In this course, PhD candidates will get an introduction into the theory of multilevel modelling, focusing on two level multilevel models with a 'continuous' response variable. In addition, participants will learn how to run basic two-level model in R.

The objective of this course is to get participants acquainted with multilevel models. These models are often used for the analysis of ‘hierarchical’ data, in which observations are nested within higher level units (e.g. repeated measures nested within individuals, or pupils nested within schools). In this type of data causes of outcomes (e.g. the performance of pupils in schools) are located both at the level of the individual (e.g., own and parental resources), and at a higher, contextual, level shared by some of the individuals (e.g. characteristics of the class and of the teacher). Because of this, the assumption of 'independent observations' is violated with hierarchical data, but multilevel modelling can easily account for that. Moreover, multilevel modelling can easily deal with missing data (in most circumstances).

This course is designed and presented by Dr. Joran Jongerling on behalf of the Erasmus Graduate School of Social Sciences and the Humanities (EGSH, www.egsh.eur.nl) of the Erasmus University Rotterdam in the Netherlands. Should you have any questions about the organization or contents of the course, please send us an email at [email protected].

What's inside

Syllabus

Errata

Introduction to Multilevel Modeling (MLM)

Random Slopes and Cross-Level Interactions

Putting it all Together

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Appeals to academics and researchers who conduct social sciences research using multilevel models

Useful for learners who are interested in learning multilevel modeling

Focuses on the application of multilevel modeling to social science research

Provides an introduction to the theory of multilevel modeling, focusing on two-level models with a continuous response variable

Covers topics such as random slopes and cross-level interactions, which are essential for understanding multilevel modeling

Assumes prior knowledge of statistics and linear regression, which may not be suitable for learners who are new to the subject

Reviews summary

Mixed opinions on multilevel modeling

According to students, the Multilevel Modeling course is a bit of a mixed bag. Learners say the content itself is good and the videos and exercises are helpful. A lot of students express appreciation for the step by step approach and also mention that some of the exercises don't make complete sense. Learners express frustration with the lack of support and dataset to follow along. There is often no support in the discussion forums and the dataset mentioned in the lessons is not provided to learners.

Course content is good.

"Good content"

"Good videos and exercises"

Exercises don't always make sense

"Exercises don't seem to fully make sense"

No dataset included

"Does not provide dataset to follow along"

"we were not provided by the data set"

No support in discussion forums

"no way to obtain support"

"no answers in discussion forums"

Career center

Learners who complete Multilevel Modeling will develop knowledge and skills that may be useful to these careers:

Statistician

As a Statistician, you will use your knowledge of mathematics and statistics to collect, analyze, interpret, and present data. Multilevel models are commonly used by statisticians, so the skills you learn in this course will be highly relevant to your work. You can use multilevel models to analyze complex data sets, such as those involving hierarchical structures. This course will help you develop the skills needed to succeed in this field.

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Data Scientist

As a Data Scientist, you will use your skills in data analysis, statistics, and programming to solve business problems. Multilevel models are often used in data science to analyze data with a hierarchical structure. This course will teach you how to use multilevel models to gain insights from complex data sets. The skills you learn in this course will make you a valuable asset to companies looking to improve their decision-making through data-driven insights.

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Market Researcher

As a Market Researcher, you will use your skills in data analysis and statistics to understand consumer behavior and market trends. Multilevel models are often used in market research to analyze data with a hierarchical structure, such as data from customers nested within stores or data from households nested within neighborhoods. This course will teach you how to use multilevel models to analyze market research data and gain insights into the factors that influence consumer behavior.

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Survey Researcher

As a Survey Researcher, you will design and conduct surveys to collect data on a variety of topics. Multilevel models are often used in survey research to analyze data with a hierarchical structure, such as data from individuals nested within households or data from students nested within schools. This course will teach you how to use multilevel models to analyze survey data and gain insights into the factors that influence individual behavior.

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Epidemiologist

As an Epidemiologist, you will study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Multilevel models are often used in epidemiology to analyze data with a hierarchical structure, such as data from individuals nested within communities or data from patients nested within hospitals.

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Economist

As an Economist, you will use your skills in mathematics and statistics to analyze economic data and develop economic models. Multilevel models are often used in economics to analyze data with a hierarchical structure, such as data from individuals nested within countries or data from firms nested within industries. This course will teach you how to use multilevel models to analyze economic data and gain insights into the factors that influence economic outcomes.

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Biostatistician

As a Biostatistician, you will use your skills in mathematics and statistics to design and analyze biological and medical research studies. Multilevel models are often used in biostatistics to analyze data with a hierarchical structure, such as data from patients nested within hospitals or data from subjects nested within clinical trials.

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Political Scientist

As a Political Scientist, you will study the political systems and processes of governments. Multilevel models are often used in political science to analyze data with a hierarchical structure, such as data from individuals nested within countries or data from states nested within countries. This course will teach you how to use multilevel models to analyze political science data and gain insights into the factors that influence political outcomes.

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Quantitative Psychologist

As a Quantitative Psychologist, you will use your skills in mathematics and statistics to design and conduct psychological research studies. Multilevel models are often used in quantitative psychology to analyze data with a hierarchical structure, such as data from individuals nested within families or data from students nested within schools.

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Educational Researcher

As an Educational Researcher, you will study the process of education in order to understand how students learn most effectively. You can use your knowledge from this course on Multilevel Modeling to analyze data from educational settings, including schools, universities, and other learning environments. You can apply multilevel models to better understand how individual, classroom, and school factors influence student learning. The skills you learn in this course will make you a valuable asset to research teams or educational institutions, as you can provide valuable insights on how to improve educational outcomes.

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Public Policy Analyst

As a Public Policy Analyst, you will use your skills in data analysis and statistics to evaluate the effectiveness of public policies. Multilevel models are often used in public policy analysis to analyze data with a hierarchical structure, such as data from individuals nested within communities or data from schools nested within districts. This course will teach you how to use multilevel models to analyze public policy data and gain insights into the factors that influence policy outcomes.

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Sociologist

As a Sociologist, you will study the social behavior of humans and the factors that influence it. Multilevel models are often used in sociology to analyze data with a hierarchical structure, such as data from individuals nested within families or data from students nested within schools. This course will teach you how to use multilevel models to analyze sociological data and gain insights into the factors that influence social behavior.

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Medical Researcher

As a Medical Researcher, you will use your skills in data analysis and statistics to design and conduct medical research studies. Multilevel models are often used in medical research to analyze data with a hierarchical structure, such as data from patients nested within hospitals or data from subjects nested within clinical trials.

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Financial Analyst

As a Financial Analyst, you will use your skills in mathematics and statistics to analyze financial data and make investment recommendations. Multilevel models are often used in financial analysis to analyze data with a hierarchical structure, such as data from stocks nested within industries or data from companies nested within countries.

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Actuary

As an Actuary, you will use your skills in mathematics and statistics to assess and manage risk. Multilevel models are often used in actuarial science to analyze data with a hierarchical structure, such as data from individuals nested within groups or data from claims nested within policies.

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Multilevel Modeling

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Mixed opinions on multilevel modeling

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