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ARD ANOVA

Source: R/ard_stats_anova.R
ard_stats_anova.Rd

Prepare ANOVA results from the stats::anova() function. Users may pass a pre-calculated stats::anova() object or a list of formulas. In the latter case, the models will be constructed using the information passed and models will be passed to stats::anova().

Usage 

ard_stats_anova(x, ...)

# S3 method for class 'anova'
ard_stats_anova(x, method_text = "ANOVA results from `stats::anova()`", ...)

# S3 method for class 'data.frame'
ard_stats_anova(
  x,
  formulas,
  method,
  method.args = list(),
  package = "base",
  method_text = "ANOVA results from `stats::anova()`",
  ...
)

Arguments

x

(anova or data.frame)
an object of class 'anova' created with stats::anova() or a data frame

...

These dots are for future extensions and must be empty.

method_text

(string)
string of the method used. Default is "ANOVA results from stats::anova()". We provide the option to change this as stats::anova() can produce results from many types of models that may warrant a more precise description.

formulas

(list)
a list of formulas

method

(string)
string of function naming the function to be called, e.g. "glm". If function belongs to a library that is not attached, the package name must be specified in the package argument.

method.args

(named list)
named list of arguments that will be passed to method.

Note that this list may contain non-standard evaluation components. If you are wrapping this function in other functions, the argument must be passed in a way that does not evaluate the list, e.g. using rlang's embrace operator {{ . }}.

package

(string)
a package name that will be temporarily loaded when function specified in method is executed.

Value

ARD data frame

Details

When a list of formulas is supplied to ard_stats_anova(), these formulas along with information from other arguments, are used to construct models and pass those models to stats::anova().

The models are constructed using rlang::exec(), which is similar to do.call().

rlang::exec(.fn = method, formula = formula, data = data, !!!method.args)

The above function is executed in withr::with_namespace(package), which allows for the use of ard_stats_anova(method) from packages, e.g. package = 'lme4' must be specified when method = 'glmer'. See example below.

Examples 

anova(
  lm(mpg ~ am, mtcars),
  lm(mpg ~ am + hp, mtcars)
) |>
  ard_stats_anova()
#> # An ARD data frame: 11 × 8
#>    variable context     stat_name stat_label stat                               
#>    <chr>    <chr>       <chr>     <chr>      <list>                             
#>  1 model_1  stats_anova term      term       mpg ~ am                           
#>  2 model_1  stats_anova df.resid… df for re… 30                                 
#>  3 model_1  stats_anova rss       Residual … 720.8966                           
#>  4 model_2  stats_anova term      term       mpg ~ am + hp                      
#>  5 model_2  stats_anova df.resid… df for re… 29                                 
#>  6 model_2  stats_anova rss       Residual … 245.4393                           
#>  7 model_2  stats_anova df        Degrees o… 1                                  
#>  8 model_2  stats_anova sumsq     Sum of Sq… 475.4573                           
#>  9 model_2  stats_anova statistic statistic  56.17789                           
#> 10 model_2  stats_anova p.value   p-value    2.920375e-08                       
#> 11 model_2  stats_anova method    method     ANOVA results from `stats::anova()`
#> # ℹ 3 more variables: fmt_fun <list>, warning <named list>, error <named list>

ard_stats_anova(
  x = mtcars,
  formulas = list(am ~ mpg, am ~ mpg + hp),
  method = "glm",
  method.args = list(family = binomial)
)
#> # An ARD data frame: 10 × 8
#>    variable context     stat_name stat_label stat                               
#>    <chr>    <chr>       <chr>     <chr>      <list>                             
#>  1 model_1  stats_anova term      term       am ~ mpg                           
#>  2 model_1  stats_anova df.resid… df for re… 30                                 
#>  3 model_1  stats_anova residual… residual.… 29.67517                           
#>  4 model_2  stats_anova term      term       am ~ mpg + hp                      
#>  5 model_2  stats_anova df.resid… df for re… 29                                 
#>  6 model_2  stats_anova residual… residual.… 19.23255                           
#>  7 model_2  stats_anova df        Degrees o… 1                                  
#>  8 model_2  stats_anova deviance  deviance   10.44261                           
#>  9 model_2  stats_anova p.value   p-value    0.001231408                        
#> 10 model_2  stats_anova method    method     ANOVA results from `stats::anova()`
#> # ℹ 3 more variables: fmt_fun <list>, warning <named list>, error <named list>

ard_stats_anova(
  x = mtcars,
  formulas = list(am ~ 1 + (1 | vs), am ~ mpg + (1 | vs)),
  method = "glmer",
  method.args = list(family = binomial),
  package = "lme4"
)
#> # An ARD data frame: 16 × 8
#>    variable context     stat_name  stat                                warning  
#>    <chr>    <chr>       <chr>      <list>                              <named l>
#>  1 model_1  stats_anova term       MODEL1                              failed t…
#>  2 model_1  stats_anova npar       2                                   failed t…
#>  3 model_1  stats_anova AIC        47.22973                            failed t…
#>  4 model_1  stats_anova BIC        50.16121                            failed t…
#>  5 model_1  stats_anova logLik     -21.61487                           failed t…
#>  6 model_1  stats_anova minus2logL 43.22973                            failed t…
#>  7 model_2  stats_anova term       MODEL2                              failed t…
#>  8 model_2  stats_anova npar       3                                   failed t…
#>  9 model_2  stats_anova AIC        35.25029                            failed t…
#> 10 model_2  stats_anova BIC        39.6475                             failed t…
#> 11 model_2  stats_anova logLik     -14.62514                           failed t…
#> 12 model_2  stats_anova minus2logL 29.25029                            failed t…
#> 13 model_2  stats_anova statistic  13.97945                            failed t…
#> 14 model_2  stats_anova df         1                                   failed t…
#> 15 model_2  stats_anova p.value    0.0001848201                        failed t…
#> 16 model_2  stats_anova method     ANOVA results from `stats::anova()` failed t…
#> # ℹ 3 more variables: stat_label <chr>, fmt_fun <list>, error <named list>