Partial Least Squares Regression and Structural Equation

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Partial Least Squares Regression and Structural Equation Models: 2016 Edition (Statistical Associates Blue Book Series 10)

This is a graduate-level introduction and illustrated tutorial on partial least squares (PLS). PLS may be used in the context of variance-based structural equation modeling, in contrast to the usual covariance-based structural equation modeling, or in the context of implementing regression models. PLS is largely a nonparametric approach to modeling, not assuming normal distributions in the data, often recommended when the focus of research is prediction rather than hypothesis testing, when sample size is not large, or in the presence of noisy data.

Why we think the new edition is important:
* Covers the much-enhanced Version 3 of SmartPLS
* Now book length at 262 pages (was 139)
* Covers the traditional PLS algorithm and consistent PLS
* Covers bootstrapped PLS, consistent bootstrapped PLS, and PLS with blindfolding
* Covers confirmatory tetrad analysis
* Covers importance-performance map analysis (IPMA)
* Covers finite-mixture segmentation (FIMIX) and prediction-oriented segmentation (POS)
* Covers multi-group analysis (MGA)
* Covers significance testing with the permutation algorithm (MICOM)

Country	USA
Author	G. David Garson
Binding	Kindle Edition
Edition	2016
Format	Kindle eBook
IsAdultProduct
Label	Statistical Associates Publishers
Manufacturer	Statistical Associates Publishers
NumberOfPages	301
PublicationDate	2014-02-08
Publisher	Statistical Associates Publishers
ReleaseDate	2014-02-08
Studio	Statistical Associates Publishers

Partial Least Squares Regression and Structural Equation Models: 2016 Edition (Statistical Associates Blue Book Series 10)

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