NORMALITY | R Documentation |
Produces tests of univariate and multivariate normality using the MVN package.
NORMALITY(data, groups, variables, verbose)
data |
A dataframe or numeric matrix where the rows are cases & the columns are the variables. |
groups |
(optional) The name of the groups variable in the dataframe, |
variables |
(optional) The names of the continuous variables in the dataframe for the analyses, e.g., variables = c('varA', 'varB', 'varC'). |
verbose |
Should detailed results be displayed in the console? |
If "groups" is not specified, the analyses will be run on all of the variables in "data". If "variables" is specified, the analyses will be run on the "variables" in "data". If "groups" is specified, the analyses will be run for every value of "groups". If verbose = TRUE, the displayed output includes descriptive statistics and tests of univariate and multivariate normality.
The returned output is a list with the following elements:
descriptives |
descriptive statistics, including skewness and kurtosis |
univariate_tests |
the univariate normality tests |
multivariate_tests |
the multivariate normality tests |
Brian P. O'Connor
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# data that simulate those from De Leo & Wulfert (2013)
NORMALITY(data = na.omit(data_CANCOR$DeLeo_2013[c(
'Unprotected_Sex','Tobacco_Use','Alcohol_Use','Illicit_Drug_Use',
'Gambling_Behavior','CIAS_Total','Impulsivity','Social_Interaction_Anxiety',
'Depression','Social_Support','Intolerance_of_Deviance','Family_Morals',
'Family_Conflict','Grade_Point_Average')]))
# data from Field et al. (2012)
NORMALITY(data = data_DFA$Field_2012,
groups = 'Group',
variables = c('Actions','Thoughts'))
# data from Tabachnik & Fidell (2013, p. 589)
NORMALITY(data = na.omit(data_CANCOR$TabFid_2019_small[c('TS','TC','BS','BC')]))
# UCLA dataset
UCLA_CCA_data <- read.csv("https://stats.idre.ucla.edu/stat/data/mmreg.csv")
colnames(UCLA_CCA_data) <- c("LocusControl", "SelfConcept", "Motivation",
"read", "write", "math", "science", "female")
summary(UCLA_CCA_data)
NORMALITY(data = na.omit(UCLA_CCA_data[c("LocusControl","SelfConcept","Motivation",
"read","write","math","science")]))
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