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Structural Equation Modelling for Ecologists and Evolutionary Biologists (SEMRPR)

1st January 2030

£500.00
Structural Equation Modelling for Ecologists and Evolutionary Biologists (SEMRPR)

Course Format

Pre Recorded

About This Course
The course is a primer on structural equation modelling (SEM) and confirmatory path analysis, with an emphasis on practical skills and applications to real-world data.

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
Introductory lectures on the concepts and mathematics of SEM; practical lectures demonstrating the application to real datasets; computer labs to expand on practical lecture materials. Participants are encouraged to bring their own data and develop their own models. Time will be set aside at the end of each day to work with participants on their models. Datasets will be made available for those who do not have existing data to bring.
Assumed quantative knowledge
Basic knowledge of linear modelling.
Assumed computer background
Proficiency with R programming language, including: importing/exporting data; manipulating data in the R environment; constructing and evaluating basic statistical models (e.g., lm()).
Equipment and software requirements
Attendees of the course must use a computer with R/RStudio installed, as well as the necessary additional R packages. Instructions on how to install the software will be provided before the start of the course. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links.

https://cran.r-project.org/
Download RStudio

UNSURE ABOUT SUITABLILITY THEN PLEASE ASK oliverhooker@prstatistics.com

Tickets

The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.
SEMRPR (PRE RECORDED)
SEMRPR (PRE RECORDED)
£ 500.00
Unlimited

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

Details

Date:
1st January 2030
Cost:
£500.00
Event Category:

Venue

Delivered remotely (United Kingdom)
Western European Time Zone, United Kingdom + Google Map

Tickets

The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.
SEMRPR (PRE RECORDED)
SEMRPR (PRE RECORDED)
£ 500.00
Unlimited