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Multivariate methods

Resources

Zuur, Alain, Elena N. Ieno, and Graham M. Smith. Analyzing Ecological Data. 2007th edition. New York ; London: Springer, 2007.

Anderson MJ, Walsh DCI (2013) PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: What null hypothesis are you testing? Ecological Monographs 83:557–574. https://doi.org/10.1890/12-2010.1

Lecture Slides

12_more_models

Corresponding Code

Download file by clicking here or view and download in the Github Repository https://github.com/jsgosnell/CUNY-BioStats/blob/master/lecture_files/13_multivariate_methods.md . You can download a single file by clicking raw; on the next page right-click the screen, select "Save as", and save the resulting .txt file (same as a .R script).

Practice!

The link above will take you to a github file showing the assignment. You can make a copy of the repository it's in to complete the assignment. This is also what the link you receive via github classroom will accomplish.

Extra Material

Structural Equation Modelling

Graphical & Latent Variable ModelingThis document focuses on structural equation modeling. It is conceptually based, and tries to generalize beyond the standard SEM treatment. It includes special emphasis on the lavaan package. Topics include: graphical models, including path analysis, bayesian networks, and network analysis, mediation, moderation, latent variable models, including principal components analysis and ‘factor analysis’, measurement models, structural equation models, mixture models, growth curves, item response theory, Bayesian nonparametric techniques, latent dirichlet allocation, and more.

Composite Variables

The Four Models You Meet in Structural Equation ModelingA linear regression is the simplest SEM, but its real power lies in expanding on that regression model. Here I discuss four types of application of Structural Equation Modeling.

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