degrees_of_freedom: Degrees of Freedom (DoF)

In easystats/parameters: Processing of Model Parameters

Degrees of Freedom (DoF)

Description

Estimate or extract degrees of freedom of models parameters.

Usage

degrees_of_freedom(model, method = "analytical", ...)

dof(model, method = "analytical", ...)

Arguments

model	A statistical model.
method	Type of approximation for the degrees of freedom. Can be one of the following: "residual" (aka "analytical") returns the residual degrees of freedom, which usually is what stats::df.residual() returns. If a model object has no method to extract residual degrees of freedom, these are calculated as n-p, i.e. the number of observations minus the number of estimated parameters. If residual degrees of freedom cannot be extracted by either approach, returns Inf. "wald" returns residual (aka analytical) degrees of freedom for models with t-statistic, 1 for models with Chi-squared statistic, and Inf for all other models. Also returns Inf if residual degrees of freedom cannot be extracted. "normal" always returns Inf. "model" returns model-based degrees of freedom, i.e. the number of (estimated) parameters. For mixed models, can also be "ml1" (or "m-l-1", approximation of degrees of freedom based on a "m-l-1" heuristic as suggested by Elff et al. 2019) or "between-within" (or "betwithin"). For mixed models of class merMod, type can also be "satterthwaite" or "kenward-roger" (or "kenward"). See 'Details'. Usually, when degrees of freedom are required to calculate p-values or confidence intervals, type = "wald" is likely to be the best choice in most cases.
...	Currently not used.

Note

In many cases, degrees_of_freedom() returns the same as df.residuals(), or n-k (number of observations minus number of parameters). However, degrees_of_freedom() refers to the model's parameters degrees of freedom of the distribution for the related test statistic. Thus, for models with z-statistic, results from degrees_of_freedom() and df.residuals() differ. Furthermore, for other approximation methods like "kenward" or "satterthwaite", each model parameter can have a different degree of freedom.

Examples

model <- lm(Sepal.Length ~ Petal.Length * Species, data = iris)
dof(model)

model <- glm(vs ~ mpg * cyl, data = mtcars, family = "binomial")
dof(model)

model <- lmer(Sepal.Length ~ Petal.Length + (1 | Species), data = iris)
dof(model)

if (require("rstanarm", quietly = TRUE)) {
  model <- stan_glm(
    Sepal.Length ~ Petal.Length * Species,
    data = iris,
    chains = 2,
    refresh = 0
  )
  dof(model)
}

easystats/parameters documentation built on Nov. 5, 2024, 12:53 p.m.