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For models that have only a single component, the tidy() and glance() methods are identical. Please see the documentation for both of those methods.

Usage

# S3 method for durbinWatsonTest
tidy(x, ...)

# S3 method for durbinWatsonTest
glance(x, ...)

Arguments

x

An object of class durbinWatsonTest created by a call to car::durbinWatsonTest().

...

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Two exceptions here are:

  • tidy() methods will warn when supplied an exponentiate argument if it will be ignored.

  • augment() methods will warn when supplied a newdata argument if it will be ignored.

Value

A tibble::tibble() with columns:

alternative

Alternative hypothesis (character).

autocorrelation

Autocorrelation.

p.value

The two-sided p-value associated with the observed statistic.

statistic

Test statistic for Durbin-Watson test.

method

Always `Durbin-Watson Test`.

Examples


# load modeling library
library(car)

# fit model
dw <- durbinWatsonTest(lm(mpg ~ wt, data = mtcars))

# summarize model fit with tidiers
tidy(dw)
#> # A tibble: 1 × 5
#>   statistic p.value autocorrelation method             alternative
#>       <dbl>   <dbl>           <dbl> <chr>              <chr>      
#> 1      1.25  0.0200           0.363 Durbin-Watson Test two.sided  

# same output for all durbinWatsonTests
glance(dw)
#> # A tibble: 1 × 5
#>   statistic p.value autocorrelation method             alternative
#>       <dbl>   <dbl>           <dbl> <chr>              <chr>      
#> 1      1.25  0.0200           0.363 Durbin-Watson Test two.sided