Structural Equation Modeling Courses and Certifications

Structural Equation Modeling with lavaan in R

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Applied Research: From Hypothesis to Structural Equation Modeling

Master the complete research journey from hypothesis formulation to advanced Structural Equation Modeling techniques for evidence-based insights across business, medicine, and social sciences.

• Swayam
• 10 weeks
• Self-Paced
• Free Online Course

The National Centre for Research Methods

Structural Equation Modelling - SEM

7 ratings

Learn advanced statistical techniques for analyzing complex relationships in data, including mediation models, factor analysis, and structural equation modeling.

• YouTube
• 2 hours 30 minutes
• Self-Paced
• Free Video

Data Science Conference

Covariance-based and Partial Least Squares SEM Modeling: Outline and Applications

Explore Structural Equation Modelling (SEM) through comparative analysis of Covariance-Based and Partial Least Squares approaches, with practical R demonstrations for evaluating complex variable relationships and testing theoretical frameworks.

• YouTube
• 1 hour 42 minutes
• Self-Paced
• Free Video

Customer Data Analytics for Marketers

12 ratings at Coursera

Enhance marketing strategies with data-driven insights. Learn statistical concepts, correlation analysis, and causality to make informed decisions and improve customer understanding.

• Coursera
• 23 hours 47 minutes
• Self-Paced
• Paid Course

Applied Multivariate Analysis with R

412 ratings at Udemy

Learn to use R software to conduct PCAs, MDSs, cluster analyses, EFAs and to estimate SEM models.

• Udemy
• 12 hours 13 minutes
• Self-Paced
• Paid Course

IIT Roorkee;  NPTEL

Marketing Research and Analysis-II

1 rating

Practical approach to marketing research and data analysis using SPSS and AMOS. Covers multivariate techniques, hypothesis testing, regression, factor analysis, and SEM for researchers and industry practitioners.

• Swayam
• 12 weeks
• Self-Paced
• Free Online Course

IIT Kharagpur;  NPTEL

Applied Multivariate Statistical Modeling

Learn to analyze and interpret multivariate data for decision-making. Covers statistical models, parameter estimation, error analysis, and real-life problem-solving in various fields like engineering, management, and data science.

• Swayam
• 12 weeks, 3-4 hours a week
• Self-Paced
• Free Online Course

Alan Turing Institute

From Causal Inference to Autoencoders, Memorization & Gene Regulation - Caroline Uhler, MIT

Exploring causal inference, autoencoders, and gene regulation through genomics and 3D genome organization. Integrates data modalities, analyzes overparameterized autoencoders, and links memorization to real-valued data retrieval.

• YouTube
• 42 minutes
• Self-Paced
• Free Video

Broad Institute

Large-Scale Differentiable Causal Discovery of Factor Graphs - Lecture and Primer

Explore large-scale causal discovery using factor directed acyclic graphs and differentiable optimization. Learn about causal representation learning for genetic perturbations and combinatorial extrapolation.

• YouTube
• 1 hour 50 minutes
• Self-Paced
• Free Video

Broad Institute

Deep End-to-end Causal Inference and Introduction to Causal Discovery

Explore deep end-to-end causal inference and discover its applications in data-driven decision-making across various domains. Learn about causal discovery, inference, and the Microsoft causal AI suite.

• YouTube
• 1 hour 52 minutes
• Self-Paced
• Free Video

Institut des Hautes Etudes Scientifiques (IHES)

Adjustment Identification Distance: A Gadjid for Causal Structure Learning

Explore the Adjustment Identification Distance (gadjid) for causal structure learning with Leonard Henckel, examining its applications and methodologies in mathematical research.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

Richard McElreath

Statistical Rethinking - Measurement Models - Lecture B07

Explore measurement models in Bayesian statistics to handle uncertainty and error in data collection and analysis.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Institut des Hautes Etudes Scientifiques (IHES)

The Science of Cause and Effect - From Theoretical Foundations to Personalized Applications

Discover the science of cause and effect with Judea Pearl, exploring theoretical foundations and personalized applications in this comprehensive UCLA lecture.

• YouTube
• 1 hour 23 minutes
• Self-Paced
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Hidden Variables in Linear Non-Gaussian Causal Models

Explore hidden variables in linear non-Gaussian causal models, using high-order cumulant information to uncover causal structures in data science applications with multiple observed variables.

• YouTube
• 32 minutes
• Self-Paced
• Free Video