Description Usage Arguments Value Author(s) References Examples

Analyzes comparison data with known factorial structures

1 2 | ```
FactorAnalysis(data, corr.matrix = FALSE, max.iteration = 50,n.factors = 0,
corr.type = "pearson")
``` |

`data` |
Matrix to store the simulated data (matrix). |

`corr.matrix` |
Correlation matrix (default is FALSE) |

`max.iteration` |
Maximum number of iterations (scalar, default is 50). |

`n.factors` |
Number of factors (scalar, default is 0). |

`corr.type` |
Type of correlation (character, default is "pearson", user can also call "spearman"). |

`$loadings` |
Factor loadings (vector, if one factor. matrix, if multiple factors) |

`$factors` |
Number of factors (scalar). |

John Ruscio

Ruscio & Roche (2011)

1 2 3 4 5 6 7 8 9 10 11 12 | ```
# create data matrix x with n = 200 cases, k = 9 variables
# 3 variables load onto each of 3 orthogonal factors
# all marginal distributions are highly skewed
x <- matrix(nrow = 200, ncol = 9)
for (i in 1:3) {
shared <- rchisq(200, 1)
for (j in 1:3) {
x[, (i - 1) * 3 + j] <- shared + rchisq(200, 1)
}
}
# perform factor analysis of data matrix x
FactorAnalysis(x)
``` |

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