Sentence examples for multivariate normality was from inspiring English sources

Multivariate normality was assessed by calculating the normalized estimate of Mardia's multivariate kurtosis coefficient [ 24].

The univariate normality assumption was checked with the one-sample Kolmogorov-Smirnov Test (SPSS) and multivariate normality was assessed with the Shapiro-Wilk goodness-of-fit test (using JMP Pro 11) on the distribution of the Mahalanobis distances.

Variables with a skewed distribution were transformed using quadratic or Log transformations and multivariate normality was tested using Henze-Zirkler's test [56].

The results indicated that multivariate normality was not observed in this model.

Multivariate normality was assessed using Mardia's Coefficient [ 28], which evaluates multivariate normality through evaluation of multivariate kurtosis.

A test of multivariate normality was used to determine the skewness of data to be used during CFA (41).

Christensen and Lund [ 14] did not rely on equation (7) to derive H, but they computed the mean of the missing genotypes conditional on the observed genotypes as: However, this is valid only for multivariate normal variables, and multivariate normality is not a good approximation for the distribution of marker covariates.

Before discussing the results, it should be mentioned that the assumptions of univariate and multivariate normality were met.

When the data fits the model, multivariate normality is assumed [ 31].

Univariate and multivariate normality were assessed through examination of the data for skewness, kurtosis, and outliers prior to SEM analyses.

Univariate and multivariate normality are assumed in structural equation modeling (SEM) because nonnormal data can produce biased parameter estimates [ 31].