Learn R Programming

sjPlot (version 2.6.1)

sjt.pca: Summary of principal component analysis as HTML table

Description

Performes a principle component analysis on a data frame or matrix (with varimax or oblimin rotation) and displays the factor solution as HTML table, or saves them as file. In case a data frame is used as parameter, the Cronbach's Alpha value for each factor scale will be calculated, i.e. all variables with the highest loading for a factor are taken for the reliability test. The result is an alpha value for each factor dimension.

Usage

sjt.pca(data, rotation = c("varimax", "oblimin"), nmbr.fctr = NULL,
  fctr.load.tlrn = 0.1, title = "Principal Component Analysis",
  var.labels = NULL, wrap.labels = 40, show.cronb = TRUE,
  show.msa = FALSE, show.var = FALSE, alternate.rows = FALSE,
  digits = 2, string.pov = "Proportion of Variance",
  string.cpov = "Cumulative Proportion", CSS = NULL, encoding = NULL,
  file = NULL, use.viewer = TRUE, remove.spaces = TRUE)

Arguments

data

A data frame that should be used to compute a PCA, or a prcomp object.

rotation

Rotation of the factor loadings. May be "varimax" for orthogonal rotation or "oblimin" for oblique transformation.

nmbr.fctr

Number of factors used for calculating the rotation. By default, this value is NULL and the amount of factors is calculated according to the Kaiser-criteria.

fctr.load.tlrn

Specifies the minimum difference a variable needs to have between factor loadings (components) in order to indicate a clear loading on just one factor and not diffusing over all factors. For instance, a variable with 0.8, 0.82 and 0.84 factor loading on 3 possible factors can not be clearly assigned to just one factor and thus would be removed from the principal component analysis. By default, the minimum difference of loading values between the highest and 2nd highest factor should be 0.1

title

String, will be used as table caption.

var.labels

Character vector with variable names, which will be used to label variables in the output.

wrap.labels

Numeric, determines how many chars of the value, variable or axis labels are displayed in one line and when a line break is inserted.

show.cronb

Logical, if TRUE (default), the cronbach's alpha value for each factor scale will be calculated, i.e. all variables with the highest loading for a factor are taken for the reliability test. The result is an alpha value for each factor dimension. Only applies when data is a data frame.

show.msa

Logical, if TRUE, shows an additional column with the measure of sampling adequacy according dor each component.

show.var

Logical, if TRUE, the proportions of variances for each component as well as cumulative variance are shown in the table footer.

alternate.rows

Logical, if TRUE, rows are printed in alternatig colors (white and light grey by default).

digits

Amount of decimals for estimates

string.pov

String for the table row that contains the proportions of variances. By default, "Proportion of Variance" will be used.

string.cpov

String for the table row that contains the cumulative variances. By default, "Cumulative Proportion" will be used.

CSS

A list with user-defined style-sheet-definitions, according to the official CSS syntax. See 'Details' or this package-vignette.

encoding

Character vector, indicating the charset encoding used for variable and value labels. Default is "UTF-8". For Windows Systems, encoding = "Windows-1252" might be necessary for proper display of special characters.

file

Destination file, if the output should be saved as file. If NULL (default), the output will be saved as temporary file and openend either in the IDE's viewer pane or the default web browser.

use.viewer

Logical, if TRUE, the HTML table is shown in the IDE's viewer pane. If FALSE or no viewer available, the HTML table is opened in a web browser.

remove.spaces

Logical, if TRUE, leading spaces are removed from all lines in the final string that contains the html-data. Use this, if you want to remove parantheses for html-tags. The html-source may look less pretty, but it may help when exporting html-tables to office tools.

Value

Invisibly returns

  • the web page style sheet (page.style),

  • the web page content (page.content),

  • the complete html-output (page.complete),

  • the html-table with inline-css for use with knitr (knitr),

  • the factor.index, i.e. the column index of each variable with the highest factor loading for each factor and

  • the removed.items, i.e. which variables have been removed because they were outside of the fctr.load.tlrn's range.

for further use.

Examples

Run this code
# NOT RUN {
# Data from the EUROFAMCARE sample dataset
library(sjmisc)
data(efc)

# recveive first item of COPE-index scale
start <- which(colnames(efc) == "c82cop1")
# recveive last item of COPE-index scale
end <- which(colnames(efc) == "c90cop9")
# auto-detection of labels
sjt.pca(efc[, start:end])
# }
# NOT RUN {
# }

Run the code above in your browser using DataLab