Structural Equation Modelling for Ecologists and Evolutionary Biologists (SEMRPR)
1st January 2030
£500.00
Course Format
Pre Recorded
About This Course
Structural equation modelling is a rapidly growing technique in ecology and evolution that unites multiple hypotheses in a single causal network. It provides an intuitive graphical representation of relationships among variables, underpinned by well-described mathematical estimation procedures. Several advances in SEM over the past few years have expanded its utility for typical ecological datasets, which include count data, missing observations, nested or hierarchical designs, and true non-linear implementations.
We will cover the basic philosophy behind SEM, provide approachable mathematical explanations of the techniques, and cover recent extensions that better unite the multiple methods of SEM. Along the way, we will work through many examples from the primary literature using the open-source statistical software R (www.r-project.org). We will draw on two popular R packages for conducting SEM, including lavaan and piecewiseSEM.
Participants are encouraged to bring their own data, as there will be opportunities throughout the course to plan, analyze, and receive feedback on structural equation models.
Intended Audiences
This course is orientated to PhD and MSc students, as well as persons in research or industry working on ecological data.
Course Details
Last up-dated – 10:03:2023
Duration – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
Teaching Format
Assumed quantative knowledge
Assumed computer background
Equipment and software requirements
https://cran.r-project.org/
Download RStudio
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK oliverhooker@prstatistics.com
PLEASE READ – CANCELLATION POLICY
Cancellations/refunds are accepted as long as the course materials have not been accessed,.
There is a 20% cancellation fee to cover administration and possible bank fess.
If you need to discuss cancelling please contact oliverhooker@prstatistics.com.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
COURSE PROGRAMME
Day 1
Approx. 7 hours
Introduction to SEM
Module 1: What is Structural Equation Modeling? Why would I use it?
Module 2: Creating multivariate causal models
Module 3: Fitting piecewise models
Readings: Grace 2010 (overview), Whalen et al. 2013 (example)
Day 2
Approx. 7 hours
SEM Using Likelihood
Module 4: Fitting Observed Variable models with covariance structures
Module 5: What does it mean to evaluate a multivariate hypothesis?
Module 6: Latent Variable models
Module 7: ANCOVA revisited & Nonlinearities
Readings: Grace & Bollen 2005, Shipley 2004
Optional Reading: Pearl 2012, Pearl 2009 (causality)
Day 3
Approx. 7 hours
Piecewise SEM
Module 8: Introduction to piecewise approach
Module 9: Incorporation of random effects models
Model 10: Autocorrelation
Reading: Shipley 2009; Lefcheck 2016
Day 4
Approx. 7 hours
Advanced Topics with Likelihood and Piecewise SEM
Module 11: Multigroup models and non-linearities
Module 12: Composite Variables
Module 13: Phylogenetically-correlated data
Module 14: Prediction using SEM
Module 15: How To Reject A Paper That Uses SEM
Readings: Grace & Julia 1999, von Hardenberg & Gonzalez‐Voyer 2013
Day 5
Approx. 3.5 hours
Open Lab and Final Presentations
Course Instructor
Dr. Jon Lefcheck
Dr. Jarett Byrnes