- statistics: h = levene_test (x)
- statistics: h = levene_test (x, group)
- statistics: h = levene_test (x, alpha)
- statistics: h = levene_test (x, testtype)
- statistics: h = levene_test (x, group, alpha)
- statistics: h = levene_test (x, group, testtype)
- statistics: h = levene_test (x, group, alpha, testtype)
- statistics: [h, pval] = levene_test (…)
- statistics: [h, pval, W] = levene_test (…)
- statistics: [h, pval, W, df] = levene_test (…)
 Perform a Levene’s test for the homogeneity of variances.
 Under the null hypothesis of equal variances, the test statistic W
 approximately follows an F distribution with df degrees of
 freedom being a vector ([k-1, N-k]).
 The p-value (1 minus the CDF of this distribution at W) is returned in
 pval.  h = 1 if the null hypothesis is rejected at the
 significance level of alpha.  Otherwise h = 0.
 Input Arguments:
 
- 
 x contains the data and it can either be a vector or matrix.
 If x is a matrix, then each column is treated as a separate group.
 If x is a vector, then the group argument is mandatory.
 NaN values are omitted.
 
- 
 group contains the names for each group.  If x is a vector, then
 group must be a vector of the same length, or a string array or cell
 array of strings with one row for each element of x.  x values
 corresponding to the same value of group are placed in the same group.
 If x is a matrix, then group can either be a cell array of
 strings of a character array, with one row per column of x in the same
 way it is used in anova1function.  If x is a matrix, then
 group can be omitted either by entering an empty array ([]) or by
 parsing only alpha as a second argument (if required to change its
 default value).
- 
 alpha is the statistical significance value at which the null
 hypothesis is rejected.  Its default value is 0.05 and it can be parsed
 either as a second argument (when group is omitted) or as a third
 argument.
 
- 
 testtype is a string determining the type of Levene’s test.  By default
 it is set to "absolute", but the user can also parse "quadratic" in order to
 perform Levene’s Quadratic test for equal variances or "median" in order to
 to perform the Brown-Forsythe’s test.  These options determine how the Z_ij
 values are computed.  If an invalid name is parsed for testtype, then
 the Levene’s Absolute test is performed.
 
 See also: 
  bartlett_test, 
  vartest2, 
  vartestn
Source Code: 
  levene_test