JWileymisc (version 1.4.1)

modelTest: Detailed Tests on Models

Description

TODO: make me!

Usage

modelTest(object, ...)
is.modelTest(x)
as.modelTest(x)
# S3 method for vglm
modelTest(object, ...)
# S3 method for lm
modelTest(object, ...)

Value

Depends on the method dispatch.

A list with two elements.

Results contains a data table of the actual estimates.

Table contains a nicely formatted character matrix.

A list with two elements.

Results contains a data table of the actual estimates.

Table contains a nicely formatted character matrix.

Arguments

object

A fitted model object.

...

Additional arguments passed to specific methods.

x

A object (e.g., list or a modelTest object) to test or attempt coercing to a modelTest object.

Examples

mtcars$cyl <- factor(mtcars$cyl)
m <- VGAM::vglm(cyl ~ qsec,
  family = VGAM::multinomial(), data = mtcars)
modelTest(m)

## clean up
rm(m, mtcars)

if (FALSE) {
mtcars$cyl <- factor(mtcars$cyl)
mtcars$am <- factor(mtcars$am)
m <- VGAM::vglm(cyl ~ qsec,
  family = VGAM::multinomial(), data = mtcars)
modelTest(m)

m <- VGAM::vglm(cyl ~ scale(qsec),
  family = VGAM::multinomial(), data = mtcars)
modelTest(m)

m2 <- VGAM::vglm(cyl ~ factor(vs) * scale(qsec),
  family = VGAM::multinomial(), data = mtcars)
modelTest(m2)

m <- VGAM::vglm(Species ~ Sepal.Length,
  family = VGAM::multinomial(), data = iris)
modelTest(m)

set.seed(1234)
sampdata <- data.frame(
  Outcome = factor(sample(letters[1:3], 20 * 9, TRUE)),
  C1 = rnorm(20 * 9),
  D3 = sample(paste0("L", 1:3), 20 * 9, TRUE))

m <- VGAM::vglm(Outcome ~ factor(D3),
  family = VGAM::multinomial(), data = sampdata)
modelTest(m)

m <- VGAM::vglm(Outcome ~ factor(D3) + C1,
  family = VGAM::multinomial(), data = sampdata)
modelTest(m)
}
m1 <- lm(mpg ~ qsec * hp, data = mtcars)
modelTest(m1)

mtcars$cyl <- factor(mtcars$cyl)
m2 <- lm(mpg ~ cyl, data = mtcars)
modelTest(m2)

m3 <- lm(mpg ~ hp * cyl, data = mtcars)
modelTest(m3)

m4 <- lm(sqrt(mpg) ~ hp * cyl, data = mtcars)
modelTest(m4)

m5 <- lm(mpg ~ sqrt(hp) * cyl, data = mtcars)
modelTest(m5)

## cleanup
rm(m1, m2, m3, m4, m5, mtcars)