Structural Equation Modelling for Ecologists and Evolutionary Biologists
(SEMR01)
https://www.prstatistics.com/course/structural-equation-modelling-for-ecologists-and-evolutionary-biologists-semr01/
This course will be delivered by Dr. Jarrett Byrnes and Dr. Jon Lefcheck
(piecewise cran package)
23 October 2017 - 27 October 2017
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. This course is particularly suited to those
studying complex interactions between animals and their environments
making it extremely useful to those studying marine mammals.
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.
Monday 23rd
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)
Tuesday 24th
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)
Wednesday 25th
Piecewise SEM
Module 8: Introduction to piecewise approach
Module 9: Incorporation of random effects models
Model 10: Autocorrelation Reading: Shipley 2009; Lefcheck 2016
Thursday 26th
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
Friday 27th
Open Lab and Final Presentations
Please email any inquiries to oliverhoo...@prstatistics.com or visit our
website www.prstatistics.com
Please feel free to distribute this material anywhere you feel is
suitable
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29th Jan – 2nd Feb 2018, Scotland, Dr. Andrew Parnell
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19th – 23rd February 2018, Wales, Dr Luca Borger, Dr. John Fieberg
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5th – 9th June 2017, Scotland, Prof. Dean Adams, Prof. Michael
Collyer, Dr. Antigoni Kaliontzopoulou
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/
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Dr. Andrew Parnell, Dr. Andrew Jackson – Date and location to be
confirmed
17. NETWORK ANAYLSIS FOR ECOLOGISTS USING R #NTWA
Dr. Marco Scotti - Date and location to be confirmed
18. MODEL BASE MULTIVARIATE ANALYSIS OF ABUNDANCE DATA USING R #MBMV0
Prof David Warton - Date and location to be confirmed
19. PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL
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2. INTRODUCTION TO BIOINFORMATICS USING LINUX #IBUL
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11th – 15th December 2017, Wales, Dr. Martin Jones
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EVOLUTIONARY BIOLOGISTS AND ECOLOGISTS #CDSR
Dr. Aline Quadros
Oliver Hooker PhD. PR statistics
2017 publications -
Ecosystem size predicts eco-morphological variability in post-glacial
diversification. Ecology and Evolution. In press.
The physiological costs of prey switching reinforce foraging
specialization. Journal of animal ecology.
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