Generic function. Generally returns things like fit indices, absolute error metrics, tests of overall model significance.
Usage
modelPerformance(object, ...)
as.modelPerformance(x)
is.modelPerformance(x)
# S3 method for class 'lm'
modelPerformance(object, ...)Value
A data.table with results.
A list with a data.table with the following elements:
- Model
A character string indicating the model type, here lm
- N_Obs
The number of observations
- AIC
Akaike Information Criterion
- BIC
Bayesian Information Criterion
- LL
log likelihood
- LLDF
log likelihood degrees of freedom
- Sigma
Residual variability
- R2
in sample variance explained
- F2
Cohen's F2 effect size R2 / (1 - R2)
- AdjR2
adjusted variance explained
- F
F value for overall model significance test
- FNumDF
numerator degrees of freedom for F test
- FDenDF
denominator degrees of freedom for F test
- P
p-value for overall model F test
Details
For lm class objects, return number of observations,
AIC, BIC, log likelihood, R2, overall model F test, and p-value.
Examples
modelPerformance(lm(mpg ~ qsec * hp, data = mtcars))
#> $Performance
#> Model N_Obs AIC BIC LL LLDF Sigma R2 F2
#> <char> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: lm 32 165.4972 172.8259 -77.74861 5 2.937243 0.7854734 3.661427
#> AdjR2 F FNumDF FDenDF P
#> <num> <num> <num> <num> <num>
#> 1: 0.7624884 34.17332 3 28 1.694676e-09
#>
#> attr(,"class")
#> [1] "modelPerformance.lm" "modelPerformance"
modelPerformance(lm(mpg ~ hp, data = mtcars))
#> $Performance
#> Model N_Obs AIC BIC LL LLDF Sigma R2 F2
#> <char> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: lm 32 181.2386 185.6358 -87.61931 3 3.862962 0.6024373 1.515327
#> AdjR2 F FNumDF FDenDF P
#> <num> <num> <num> <num> <num>
#> 1: 0.5891853 45.4598 1 30 1.787835e-07
#>
#> attr(,"class")
#> [1] "modelPerformance.lm" "modelPerformance"
if (FALSE) { # \dontrun{
modelPerformance(lm(mpg ~ 0 + hp, data = mtcars))
modelPerformance(lm(mpg ~ 1, data = mtcars))
modelPerformance(lm(mpg ~ 0, data = mtcars))
} # }