[R-sig-eco] Structural Equation Modelling for Ecologists and Evolutionary Biologists (SEMR02)

[Oliver Hooker]

Structural Equation Modelling for Ecologists and Evolutionary Biologists 
(SEMR02)

https://www.prstatistics.com/course/structural-equation-modelling-for-ecologists-and-evolutionary-biologists-semr02/

This course will be delivered by Dr. Jonathan Lefcheck (author of the 
piecewise package) from the 19th - 23rd November 2018 in Glasgow City 
Centre.

Course Overview:
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, and nested or 
hierarchical designs.

We will cover the basic philosophy behind SEM, provide approachable 
mathematical explanations of the techniques, and cover recent extensions 
to mixed effects models and non-normal distributions. 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.

Course Programme
Day 1
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
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
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
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
Open Lab and Final Presentations

Email oliverhooker using prstatistics.com

Check out our sister sites,
www.PRstatistics.com (Ecology and Life Sciences)
www.PRinformatics.com (Bioinformatics and data science)
www.PSstatistics.com (Behaviour and cognition)


-- 
Oliver Hooker PhD.
PR statistics

2018 publications -

Alternative routes to piscivory: Contrasting growth trajectories in 
brown trout (Salmo trutta) ecotypes exhibiting contrasting life history 
strategies. Ecology of Freshwater Fish. DOI to follow

Phenotypic and resource use partitioning amongst sympatric lacustrine 
brown trout, Salmo trutta. Biological Journal of the Linnean Society. 
DOI 10.1093/biolinnean/bly032

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