Structural Equation Modeling Done Right - Online Course
A 3-Day Livestream Seminar Taught by
Rex B. Kline10:00am-12:30pm (convert to your local time)
1:30pm-3:30pm
Techniques of structural equation modeling (SEM) have become widely used in many disciplines, including psychology, education, medicine, management, epidemiology, and sociology. According to Google Scholar, there were more than 28,000 articles published in 2022 that included the phrase “structural equation model.”
Unfortunately, there are problems in many, if not most, published SEM studies. One common shortcoming is incomplete reporting about the results, especially about model fit – that is, whether the implications of the researcher’s model are consistent with the data. Incomplete reporting means that readers may be unable to adequately judge the trustworthiness or scientific merit of the results.
This introductory-level 3-day seminar (1) introduces basic concepts and techniques in SEM while (2) emphasizing best practices – that is, SEM done right. The main goal is to help participants distinguish their own work in SEM by following best practices and avoiding common mistakes.
Starting November 9, we are offering this seminar as a 3-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.
*We understand that finding time to participate in livestream courses can be difficult. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.
Closed captioning is available for all live and recorded sessions. Live captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.
More details about the course content
This seminar begins with the study of core SEM techniques, such as path analysis for estimating causal effects of observed variables and confirmatory factor analysis (CFA) for estimating causal effects of latent variables in measurement models. These techniques are described with examples of applications using real data sets.
Complete and transparent assessment of model fit includes evaluation of both global and local model fit. Global fit concerns the overall or average correspondence between model and data, and local fit concerns the accuracy of predictions based on the model for pairs of measured variables. Local fit assessment can also be described as inspecting model residuals. In too many published SEM studies, little or no information about local fit is reported. This omission conflicts with well-established reporting standards for SEM studies.
This seminar begins with the study of core SEM techniques, such as path analysis for estimating causal effects of observed variables and confirmatory factor analysis (CFA) for estimating causal effects of latent variables in measurement models. These techniques are described with examples of applications using real data sets.
Complete and transparent assessment of model fit includes evaluation of both global and local model fit. Global fit concerns the overall or average correspondence between model and data, and local fit concerns the accuracy of predictions based on the model for pairs of measured variables. Local fit assessment can also be described as inspecting model residuals. In too many published SEM studies, little or no information about local fit is reported. This omission conflicts with well-established reporting standards for SEM studies.
Computing
Syntax, data, and output files for all example analyses are available for the R package lavaan, which is freely available, as is the R computing environment itself.
All files can be downloaded by participants from the seminar website and opened with any basic text editor. This means that participants can reproduce all example analyses in R or simply view the contents of these files if they use different SEM software. However, prior experience with lavaan or any other SEM software is not required to benefit from this seminar. Instead, we will emphasize concepts and practices that should be known by users of any SEM computer tool.
Participants who want to use lavaan in their own analyses can find a good tutorial website here.
If you’d like to take this course but are concerned that you don’t know enough R, there are excellent online resources for learning the basics. Here are our recommendations.
Syntax, data, and output files for all example analyses are available for the R package lavaan, which is freely available, as is the R computing environment itself.
All files can be downloaded by participants from the seminar website and opened with any basic text editor. This means that participants can reproduce all example analyses in R or simply view the contents of these files if they use different SEM software. However, prior experience with lavaan or any other SEM software is not required to benefit from this seminar. Instead, we will emphasize concepts and practices that should be known by users of any SEM computer tool.
Participants who want to use lavaan in their own analyses can find a good tutorial website here.
If you’d like to take this course but are concerned that you don’t know enough R, there are excellent online resources for learning the basics. Here are our recommendations.
Who should register?
It is expected that participants in this introductory-level seminar will be graduate students, faculty members, or applied researchers who seek to know more about the potential to apply SEM in their own work. Basic familiarity with multiple regression and exploratory factor analysis (EFA) is assumed, but no prior experience using SEM software is required.
The presentation will be conceptually rather than mathematically oriented. The overall goal of the seminar is to help participants distinguish their SEM studies through the use of best analysis and reporting practices.
Optional articles in PDF format for course topics and syntax, as well as data and output files in plain text format for analysis examples can be downloaded by participants from the seminar website.
It is expected that participants in this introductory-level seminar will be graduate students, faculty members, or applied researchers who seek to know more about the potential to apply SEM in their own work. Basic familiarity with multiple regression and exploratory factor analysis (EFA) is assumed, but no prior experience using SEM software is required.
The presentation will be conceptually rather than mathematically oriented. The overall goal of the seminar is to help participants distinguish their SEM studies through the use of best analysis and reporting practices.
Optional articles in PDF format for course topics and syntax, as well as data and output files in plain text format for analysis examples can be downloaded by participants from the seminar website.
Seminar outline
Reporting results from SEM studies
- Common reporting problems and deficiencies
- Reporting standards for published SEM studies
- Addressing equivalent models
Families of SEM technique and basic model types
- Traditional, composite, and nonparametric SEM
- Type of traditional SEM models
- Model diagrams
Analysis considerations
- Sample size requirements
- Data preparation
- Options for SEM software
Model fit assessment
- Global fit statistics
- Types of model residuals
- Modification indexes and cautions
Reporting results from SEM studies
- Common reporting problems and deficiencies
- Reporting standards for published SEM studies
- Addressing equivalent models
Families of SEM technique and basic model types
- Traditional, composite, and nonparametric SEM
- Type of traditional SEM models
- Model diagrams
Analysis considerations
- Sample size requirements
- Data preparation
- Options for SEM software
Model fit assessment
- Global fit statistics
- Types of model residuals
- Modification indexes and cautions
Payment information
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.