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Print MID Models

Source: R/print_mid.R
print.mid.Rd

print() methods for a fitted MID model ("mid") or a collection of models ("mids").

Usage

# S3 method for class 'mid'
print(x, digits = max(3L, getOption("digits") - 2L), main.effects = FALSE, ...)

# S3 method for class 'mids'
print(x, max.nmodels = 1L, ...)

Arguments

x

a "mid" or "mids" object to be printed.

digits

an integer specifying the number of significant digits for printing.

main.effects

logical. If TRUE, the MID values of each main effect are also printed (only applicable for single "mid" objects).

...

arguments to be passed to other methods.

max.nmodels

an integer specifying the maximum number of models to print for a "midlist" collection.

Value

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

print.mids() returns the original "mids" object invisibly.

Details

By default, the print() method for "mid" objects provides a quick overview of the model structure by listing the number of main effect and interaction terms. If main.effects = TRUE is specified, the method will also print the contribution of each main effect at its sample points, providing a more detailed look at the model's components.

For a collection of models in the structure-of-array format ("midrib"), the method prints a summarized overview. For array-of-structures collections ("midlist"), it prints the first few models up to max.nmodels.

See also

interpret, summary.mid

Examples

data(cars, package = "datasets")
mid <- interpret(dist ~ speed, cars)
#> 'model' not passed: response variable in 'data' is used

# Default print provides a concise summary
print(mid)
#> 
#> Call:
#> interpret(formula = dist ~ speed, data = cars)
#> 
#> Intercept: 42.98
#> 
#> Main Effects:
#> 1 main effect term
#> 
#> Uninterpreted Variation Ratio: 0.22636

# Setting main.effects = TRUE prints the contributions of each main effect
print(mid, main.effects = TRUE)
#> 
#> Call:
#> interpret(formula = dist ~ speed, data = cars)
#> 
#> Intercept: 42.98
#> 
#> Main Effects:
#> ---
#> $speed
#>        4        7        8       10       11       12       13       14 
#> -36.9800 -29.9800 -31.1050 -18.3550 -20.4800 -21.4800  -7.9800   7.5200 
#>       15       16       17       18       19       20       22       24 
#>  -9.6467  -6.9800  -2.3133  21.5200   7.0200   7.4200  13.1629  48.3057 
#>       25 
#>  42.0200 
#> 
#> Uninterpreted Variation Ratio: 0.22636