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Programme

The course is directed to Ph.D. students, post-docs and researchers in biology/environmental science with basic statistical knowledge (e.g. linear regression and one-way ANOVA) using R, SPSS, Statistica, etc.

 
All lectures are in English.
 
NOTE: Before class tutorials, data, R packages and suggested readings are provided in http://jarrettbyrnes.info/ubc_sem/
 
NOTE: Participants should bring their own laptops to the course.
 
Topics
DAY 1, 25-3-2013
  Lectures:
  - What is SEM? How can it be part of your research program? 
  -

SEM as a process: Creating multivariate causal models

  -

Fitting piecewise models

  Exercises:
  - Creating causal conceptual models
  -

Piecewise model creation

     

DAY 2, 26-3-2013

  Lectures:
  - Fitting Observed Variable models with covariance structures
  -

What does it mean to evaluate a multivariate hypothesis?

  -

ANCOVA revisited & Nonlinearities

  Exercises:
  - Fitting observed variable structural equation models in R
     

DAY 3, 27-3-2013

  Lectures:
  - Multigroup models
  -

Latent Variable models

 

Exercises:

  - Multigroup analysis and the introduction of the latent variable
     

DAY 4, 28-3-2013

  Lectures:
  - Composite Variables
  -

Revisiting piecewise approaches for nonlinear and hierarchical data

  -

How to Fool Yourself with SEM (sensu Kline)

 

Exercises:

  - Composites & Other Advanced Techniques
     

DAY 5, 29-3-2013

  Open Consultation