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jmv

pca

Principal Component Analysis

Description

Principal Component Analysis

Usage

pca(
  data,
  vars,
  nFactorMethod = "parallel",
  nFactors = 1,
  minEigen = 1,
  rotation = "varimax",
  hideLoadings = 0.3,
  sortLoadings = FALSE,
  screePlot = FALSE,
  eigen = FALSE,
  factorCor = FALSE,
  factorSummary = FALSE,
  kmo = FALSE,
  bartlett = FALSE
)

Arguments

`data`	the data as a data frame
`vars`	a vector of strings naming the variables of interest in `data`
`nFactorMethod`	`'parallel'` (default), `'eigen'` or `'fixed'`, the way to determine the number of factors
`nFactors`	an integer (default: 1), the number of components in the model
`minEigen`	a number (default: 1), the minimal eigenvalue for a component to be included in the model
`rotation`	`'none'`, `'varimax'` (default), `'quartimax'`, `'promax'`, `'oblimin'`, or `'simplimax'`, the rotation to use in estimation
`hideLoadings`	a number (default: 0.3), hide loadings below this value
`sortLoadings`	`TRUE` or `FALSE` (default), sort the factor loadings by size
`screePlot`	`TRUE` or `FALSE` (default), show scree plot
`eigen`	`TRUE` or `FALSE` (default), show eigenvalue table
`factorCor`	`TRUE` or `FALSE` (default), show factor correlations
`factorSummary`	`TRUE` or `FALSE` (default), show factor summary
`kmo`	`TRUE` or `FALSE` (default), show Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (MSA) results
`bartlett`	`TRUE` or `FALSE` (default), show Bartlett's test of sphericity results

Value

A results object containing:

`results$loadings`					a table
`results$factorStats$factorSummary`					a table
`results$factorStats$factorCor`					a table
`results$modelFit$fit`					a table
`results$assump$bartlett`					a table
`results$assump$kmo`					a table
`results$eigen$initEigen`					a table
`results$eigen$screePlot`					an image

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$loadings$asDF

as.data.frame(results$loadings)

Examples

data('iris')

pca(iris, vars = vars(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width))

#
#  PRINCIPAL COMPONENT ANALYSIS
#
#  Component Loadings
#  ----------------------------------------
#                    1         Uniqueness
#  ----------------------------------------
#    Sepal.Length     0.890        0.2076
#    Sepal.Width     -0.460        0.7883
#    Petal.Length     0.992        0.0168
#    Petal.Width      0.965        0.0688
#  ----------------------------------------
#    Note. 'varimax' rotation was used
#

jmv

The 'jamovi' Analyses

v1.2.23

GPL (>= 2)

Authors

Ravi Selker, Jonathon Love, Damian Dropmann

Initial release

2020-06-26

pca

Description

Usage

Arguments

Value

Examples

jmv

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