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PCovR (version 2.7.2)

Principal Covariates Regression

Description

Analyzing regression data with many and/or highly collinear predictor variables, by simultaneously reducing the predictor variables to a limited number of components and regressing the criterion variables on these components (de Jong S. & Kiers H. A. L. (1992) ). Several rotation and model selection options are provided.

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Version

Install

install.packages('PCovR')

Monthly Downloads

248

Version

2.7.2

License

GPL (>= 2)

Maintainer

Kristof Meers

Last Published

October 26th, 2023

Functions in PCovR (2.7.2)

PCovR-package

Principal Covariates Regression
promin

Promin rotation
tarrotob

Oblique target rotation
alexithymia

Effect of alexithymia on depression and self-esteem
pcovr_est

Estimation of Principal Covariates Regression parameters, given a prespecified weighting value and number of components
wvarim

Weighted varimax
ErrorRatio

Error variance ratio
SortLoadings

Sorting a component loading matrix
psychiatrists

Effect of psychiatric symptoms on toxicomania, schizophrenia, depression and anxiety disorder
pcovr

Full Principal covariates regression analysis of a specific data set