parameters (version 0.4.0)

model_parameters.mixor: Mixed Model Parameters

Description

Parameters of (linear) mixed models.

Usage

# S3 method for mixor
model_parameters(
  model,
  ci = 0.95,
  effects = c("all", "fixed", "random"),
  bootstrap = FALSE,
  iterations = 1000,
  standardize = NULL,
  exponentiate = FALSE,
  ...
)
# S3 method for merMod
model_parameters(
  model,
  ci = 0.95,
  bootstrap = FALSE,
  df_method = "wald",
  iterations = 1000,
  standardize = NULL,
  exponentiate = FALSE,
  ...
)
# S3 method for glmmTMB
model_parameters(
  model,
  ci = 0.95,
  bootstrap = FALSE,
  iterations = 1000,
  component = c("all", "conditional", "zi", "zero_inflated"),
  standardize = NULL,
  exponentiate = FALSE,
  ...
)

Arguments

model

A mixed model.

ci

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

effects

Should parameters for fixed effects, random effects or both be returned? Only applies to mixed models. May be abbreviated.

bootstrap

Should estimates be based on bootstrapped model? If TRUE, then arguments of Bayesian regressions apply (see also parameters_bootstrap()).

iterations

The number of bootstrap replicates. This only apply in the case of bootstrapped frequentist models.

standardize

The method used for standardizing the parameters. Can be "refit", "posthoc", "smart", "basic" or NULL (default) for no standardization. See 'Details' in standardize_parameters.

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.

...

Arguments passed to or from other methods.

df_method

Method for computing degrees of freedom for p values, standard errors and confidence intervals (CI). May be "wald" (default, see degrees_of_freedom), "ml1" (see dof_ml1), "satterthwaite" (see dof_satterthwaite) or "kenward" (see dof_kenward).

component

Model component for which parameters should be shown. May be one of "conditional", "precision" (betareg), "scale" (ordinal), "extra" (glmx) or "all".

Value

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

See Also

standardize_names() to rename columns into a consistent, standardized naming scheme.

Examples

# NOT RUN {
library(parameters)
library(lme4)
library(glmmTMB)

model <- lmer(mpg ~ wt + (1 | gear), data = mtcars)
model_parameters(model)

model <- glmmTMB(
  count ~ spp + mined + (1 | site),
  ziformula = ~mined,
  family = poisson(),
  data = Salamanders
)
model_parameters(model)
# }
# NOT RUN {
model <- lme4::lmer(mpg ~ wt + (1 | gear), data = mtcars)
model_parameters(model, bootstrap = TRUE, iterations = 50)
# }
# NOT RUN {
# }