Summarize MID Models

For "mid" objects, an S3 method of summary() prints a comprehensive summary of a fitted MID model.

Usage

# S3 method for class 'mid'
summary(object, digits = max(3L, getOption("digits") - 2L), top.n = 10L, ...)

Arguments

object

a "mid" object to be summarized.

digits

the number of significant digits for printing numeric values.

top.n

the maximum number of top-ranked terms to be printed in the MID importance table.

...

arguments to be passed to other methods (not used in this method).

Value

summary.mid() returns the original "mid" object invisibly.

Details

The S3 method summary.mid() generates a comprehensive overview of the fitted MID model. The output includes the following components: (1) "Call" - the function call used to fit the MID model. (2) "Uninterpreted Variation Ratio" - a key metric indicating the proportion of the target model's variance that is not explained by the MID model. Lower values suggest a better fit. (3) "Residuals" - a five-number summary (Min, 1Q, Median, 3Q, Max) of the working residuals. This aids in assessing model fit and identifying potential biases. (4) "Encoding" - a summary of the encoding schemes used for each variable in the MID model. (5) "Importance" - a list of the top terms ranked by their MID importance, which quantifies their average contribution to the model's predictions.

See also

interpret, print.mid

Examples

# Summarize a fitted MID model
data(cars, package = "datasets")
mid <- interpret(dist ~ speed, cars)
#> 'model' not passed: response variable in 'data' is used
summary(mid)
#> 
#> Call:
#> interpret(formula = dist ~ speed, data = cars)
#> 
#> Uninterpreted Variation Ratio:
#> [1] 0.22636
#> 
#> Residuals:
#>       Min        1Q    Median        3Q       Max 
#> -24.50000  -8.06250  -0.33333   8.37500  29.50000 

#> 
#> Encoding:
#>       main.effect
#> speed  linear(17)
#> 
#> Importance:
#>    term importance order
#> 1 speed     18.138     1