bootTest | R Documentation |

`bootTest`

is a bootstrap test for whether an ordinal dataset is consistent with being
a discretization of a multivariate normal dataset.

bootTest(my.data, B = 1000, verbose = TRUE)

`my.data` |
A dataset containing ordinal data. Must contain only integer values. |

`B` |
Number of bootstrap samples. |

`verbose` |
If true, bootstrap progress is printed to the console. |

p-value associated with the underlying normality hypothesis.

Njål Foldnes & Steffen Grønneberg (2019) Pernicious Polychorics: The Impact and Detection of Underlying Non-normality, Structural Equation Modeling: A Multidisciplinary Journal, DOI: 10.1080/10705511.2019.1673168

set.seed(1) norm.data <- MASS::mvrnorm(300, m=rep(0,3), Sigma=cov(MASS::mvrnorm(15, mu=rep(0,3), Sigma=diag(3)))) disc.data <- apply(norm.data,2, cut, breaks = c(-Inf, 0,1, Inf), labels=FALSE)# normal data discretized pvalue <- bootTest(disc.data, B=500) #no support for underlying non-normality

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