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Test if k samples are from populations with equal variances.

Usage

ols_test_bartlett(data, ...)

# S3 method for default
ols_test_bartlett(data, ..., group_var = NULL)

Arguments

data

A data.frame or tibble.

...

Columns in data.

group_var

Grouping variable.

Value

ols_test_bartlett returns an object of class "ols_test_bartlett". An object of class "ols_test_bartlett" is a list containing the following components:

fstat

f statistic

pval

p-value of fstat

df

degrees of freedom

Details

Bartlett's test is used to test if variances across samples is equal. It is sensitive to departures from normality. The Levene test is an alternative test that is less sensitive to departures from normality.

References

Snedecor, George W. and Cochran, William G. (1989), Statistical Methods, Eighth Edition, Iowa State University Press.

See also

Other heteroskedasticity tests: ols_test_breusch_pagan(), ols_test_f(), ols_test_score()

Examples

# using grouping variable
if (require("descriptr")) {
  library(descriptr)
  ols_test_bartlett(mtcarz, 'mpg', group_var = 'cyl')
}
#> Loading required package: descriptr
#> 
#> Attaching package: 'descriptr'
#> The following object is masked from 'package:olsrr':
#> 
#>     hsb
#> 
#>     Bartlett's Test of Homogenity of Variances    
#> ------------------------------------------------
#> Ho: Variances are equal across groups
#> Ha: Variances are unequal for atleast two groups
#> 
#>         Test Summary          
#>  -----------------------------
#>  DF            =    2 
#>  Chi2          =    8.39345 
#>  Prob > Chi2   =    0.01504477 

# using variables
ols_test_bartlett(hsb, 'read', 'write')
#> 
#>     Bartlett's Test of Homogenity of Variances    
#> ------------------------------------------------
#> Ho: Variances are equal across groups
#> Ha: Variances are unequal for atleast two groups
#> 
#>         Data          
#>  ---------------------
#>  Variables: read write 
#> 
#>         Test Summary         
#>  ----------------------------
#>  DF            =    1 
#>  Chi2          =    1.222871 
#>  Prob > Chi2   =    0.2687979