insight (version 0.14.3)

model_info: Access information from model objects

Description

Retrieve information from model objects.

Usage

model_info(x, ...)
# S3 method for default
model_info(x, verbose = TRUE, ...)

Arguments

x

A fitted model.

...

Currently not used.

verbose

Toggle off warnings.

Value

A list with information about the model, like family, link-function etc. (see 'Details').

Details

model_info() returns a list with information about the model for many different model objects. Following information is returned, where all values starting with is_ are logicals.

• is_binomial: family is binomial (but not negative binomial)

   \item `is_bernoulli`: special case of binomial models: family is
   Bernoulli
  \item `is_poisson`: family is poisson
  \item `is_negbin`: family is negative binomial
  \item `is_count`: model is a count model (i.e. family is either
   poisson or negative binomial)
  \item `is_beta`: family is beta
  \item `is_betabinomial`: family is beta-binomial
  \item `is_dirichlet`: family is dirichlet
  \item `is_exponential`: family is exponential (e.g. Gamma or Weibull)
  \item `is_logit`: model has logit link
  \item `is_probit`: model has probit link
  \item `is_linear`: family is gaussian
  \item `is_tweedie`: family is tweedie
  \item `is_ordinal`: family is ordinal or cumulative link
  \item `is_cumulative`: family is ordinal or cumulative link
  \item `is_multinomial`: family is multinomial or categorical link
  \item `is_categorical`: family is categorical link
  \item `is_censored`: model is a censored model (has a censored
   response, including survival models)
  \item `is_truncated`: model is a truncated model (has a truncated
   response)
  \item `is_survival`: model is a survival model
  \item `is_zero_inflated`: model has zero-inflation component
  \item `is_hurdle`: model has zero-inflation component and is a
   hurdle-model (truncated family distribution)
  \item `is_dispersion`: model has dispersion component
  \item `is_mixed`: model is a mixed effects model (with random
   effects)
  \item `is_multivariate`: model is a multivariate response model
   (currently only works for *brmsfit* objects)
  \item `is_trial`: model response contains additional information
   about the trials
  \item `is_bayesian`: model is a Bayesian model
  \item `is_gam`: model is a generalized additive model
  \item `is_anova`: model is an Anova object
  \item `is_ttest`: model is an an object of class `htest`,
   returned by `t.test()`
  \item `is_correlation`: model is an an object of class
   `htest`, returned by `cor.test()`
  \item `is_ranktest`: model is an an object of class `htest`,
   returned by `cor.test()` (if Spearman's rank correlation),
   `wilcox.text()` or `kruskal.test()`.
  \item `is_levenetest`: model is an an object of class `anova`,
   returned by `car::leveneTest()`.
  \item `is_onewaytest`: model is an an object of class `htest`,
   returned by `oneway.test()`
  \item `is_proptest`: model is an an object of class `htest`,
   returned by `prop.test()`
  \item `is_binomtest`: model is an an object of class `htest`,
   returned by `binom.test()`
  \item `is_chi2test`: model is an an object of class `htest`,
   returned by `chisq.test()`
  \item `is_xtab`: model is an an object of class `htest` or
   `BFBayesFactor`, and test-statistic stems from a contingency table
   (i.e. `chisq.test()` or `BayesFactor::contingencyTableBF()`).
  \item `link_function`: the link-function
  \item `family`: the family-object
  \item `n_obs`: number of observations
  \item `model_terms`: a list with all model terms, including terms
   such as random effects or from zero-inflated model parts.
  

Examples

# NOT RUN {
ldose <- rep(0:5, 2)
numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16)
sex <- factor(rep(c("M", "F"), c(6, 6)))
SF <- cbind(numdead, numalive = 20 - numdead)
dat <- data.frame(ldose, sex, SF, stringsAsFactors = FALSE)
m <- glm(SF ~ sex * ldose, family = binomial)

model_info(m)
# }
# NOT RUN {
library(glmmTMB)
data("Salamanders")
m <- glmmTMB(
  count ~ spp + cover + mined + (1 | site),
  ziformula = ~ spp + mined,
  dispformula = ~DOY,
  data = Salamanders,
  family = nbinom2
)
# }
# NOT RUN {
model_info(m)
# }