parameters (version 0.13.0)

model_parameters.PMCMR: Parameters from Hypothesis Testing

Description

Parameters from Hypothesis Testing.

Usage

# S3 method for PMCMR
model_parameters(model, ...)
# S3 method for glht
model_parameters(model, ci = 0.95, exponentiate = FALSE, verbose = TRUE, ...)

Arguments

model

Object of class glht (multcomp) or of class PMCMR, trendPMCMR or osrt (PMCMRplus).

...

Arguments passed to or from other methods. For instance, when bootstrap = TRUE, arguments like ci_method are passed down to describe_posterior.

ci

Confidence Interval (CI) level. Default to 0.95 (95%).

exponentiate

Logical, indicating whether or not to exponentiate the the coefficients (and related confidence intervals). This is typical for, say, logistic regressions, or more generally speaking: for models with log or logit link. Note: standard errors are also transformed (by multiplying the standard errors with the exponentiated coefficients), to mimic behaviour of other software packages, such as Stata. For compare_parameters(), exponentiate = "nongaussian" will only exponentiate coefficients for all models except those from Gaussian family.

verbose

Toggle warnings and messages.

Value

A data frame of indices related to the model's parameters.

Examples

# NOT RUN {
if (require("multcomp", quietly = TRUE)) {
  # multiple linear model, swiss data
  lmod <- lm(Fertility ~ ., data = swiss)
  mod <- glht(
    model = lmod,
    linfct = c(
      "Agriculture = 0",
      "Examination = 0",
      "Education = 0",
      "Catholic = 0",
      "Infant.Mortality = 0"
    )
  )
  model_parameters(mod)
}
if (require("PMCMRplus", quietly = TRUE)) {
  model <- kwAllPairsConoverTest(count ~ spray, data = InsectSprays)
  model_parameters(model)
}
# }