"Structural Equation Modelling for Ecologists and Evolutionary Biologists”
Delivered by Dr. Jarret Byrnes and Dr. Jon Lefcheck http://www.prstatistics.com/course/structural-equation-modelling-for- ecologists-and-evolutionary-biologists-semr01/ This course will run from 30th October �C 30th November 2017 at Margam Park Discovery Centre, Wales. Course only and all inclusive packages are available. 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 (SEM) 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, analyse, and receive feedback on structural equation models. Course content is as follows 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 Please email any inquiries to [email protected] or visit our website www.prstatistics.com Please feel free to distribute this material anywhere you feel is suitable Our other courses 1. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR #SIMM 28th Feb �C 3rd Mar 2017, Scotland, Dr. Andrew Parnell, Dr. Andrew Jackson http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r- simm03/ 2. NETWORK ANAYLSIS FOR ECOLOGISTS USING R #NTWA 6th �C 10th March 2017, Scotland, Dr. Marco Scotti http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/ 3. 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ADVANCING IN STATISTICAL MODELLING USING R #ADVR 11th �C 15th December 2017, Wales, Dr. Luc Bussiere, Dr. Tom Houslay, Dr. Ane Timenes Laugen, http://www.prstatistics.com/course/advancing-statistical-modelling-using-r- advr07/ 21. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING #IBHM 29th Jan �C 2nd Feb, Scotland, Dr. Andrew Parnell http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical- modelling-using-r-ibhm02/ 22. ANIMAL MOVEMENT ECOLOGY (February 2018) #ANME ??th - ??th February, Wales, Dr Luca Borger, Dr. John Fieberg 23. AQUATIC TELEMENTRY DATA ANALYSIS USIR R (TBC) #ATDAR Oliver Hooker PhD. PR statistics 3/1 128 Brunswick Street Glasgow G1 1TF +44 (0) 7966500340 www.prstatistics.com www.prstatistics.com/organiser/oliver-hooker/
