Print a hierarchial_lm Class Object

Print the content of a 'hierarchical_lm`-class object.

Usage

# S3 method for class 'hierarchical_lm'
print(
  x,
  digits = 4,
  signif.stars = getOption("show.signif.stars"),
  eps.Pvalue = 0.001,
  ...
)

Arguments

x

A hierarchical_lm-class object, usually the output of hierarchical_lm().

digits

The minimum number of significant digits to be used for most numbers. To be used by the print method of anova-class objects.

signif.stars

Logical. To be used by the print method of anova-class objects.

eps.Pvalue

To be passed to format.pval(). It controls how small p-values are displayed. Default is .001. That is, p-values less than .001 will be displayed as <.001.

...

Optional arguments. To be passed to the print method of anova-class objects.

Value

x is returned invisibly. Called for its side effect.

Details

The printout is very similar to that of the print method of an anova object. It simply overrides the default values for some arguments, notably esp.Pvalue to prevent small p-values to be presented in scientific notation.

See also

hierarchical_lm()

Author

Shu Fai Cheung https://orcid.org/0000-0002-9871-9448

Examples

dat <- data_test1
lm1 <- lm(y ~ x1 + x2, dat)
lm2 <- lm(y ~ x1 + x2 + x3 + x4, dat)
lm3 <- lm(y ~ x1 + cat1 + cat2 + x2 + x3 + x4, dat)
lm4 <- lm(y ~ x1 + x2*x3 + x4, dat)

hierarchical_lm(lm1, lm3, lm2)
#> Analysis of Variance Table
#> 
#> Model 1: y ~ x1 + x2
#> Model 2: y ~ x1 + x2 + x3 + x4
#> Model 3: y ~ x1 + cat1 + cat2 + x2 + x3 + x4
#>   adj.R.sq   R.sq R.sq.change Res.Df   RSS Df Sum of Sq      F Pr(>F)    
#> 1   0.5090 0.5189     0.00000     97 55.83                               
#> 2   0.7269 0.7380     0.21906     95 30.41  2    25.419 39.717 <0.001 ***
#> 3   0.7270 0.7518     0.01385     90 28.80  5     1.607  1.004   0.42    
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
hierarchical_lm(lm1, lm2, lm4)
#> Analysis of Variance Table
#> 
#> Model 1: y ~ x1 + x2
#> Model 2: y ~ x1 + x2 + x3 + x4
#> Model 3: y ~ x1 + x2 * x3 + x4
#>   adj.R.sq   R.sq R.sq.change Res.Df   RSS Df Sum of Sq      F Pr(>F)    
#> 1   0.5090 0.5189      0.0000     97 55.83                               
#> 2   0.7269 0.7380      0.2191     95 30.41  2    25.419 39.320 <0.001 ***
#> 3   0.7242 0.7382      0.0002     94 30.38  1     0.024  0.073  0.787    
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1