This functions tries to get the data that was used to fit the model and returns it as data frame.

get_data(x, ...)

# S3 method for hurdle
get_data(x, component = c("all", "conditional", "zi",
  "zero_inflated", "dispersion"), ...)

# S3 method for glmmTMB
get_data(x, effects = c("all", "fixed", "random"),
  component = c("all", "conditional", "zi", "zero_inflated",
  "dispersion"), ...)

# S3 method for merMod
get_data(x, effects = c("all", "fixed", "random"), ...)

# S3 method for rlmerMod
get_data(x, effects = c("all", "fixed", "random"),
  ...)

# S3 method for mixed
get_data(x, effects = c("all", "fixed", "random"), ...)

# S3 method for clmm
get_data(x, effects = c("all", "fixed", "random"), ...)

# S3 method for lme
get_data(x, effects = c("all", "fixed", "random"), ...)

# S3 method for gee
get_data(x, effects = c("all", "fixed", "random"), ...)

# S3 method for rqss
get_data(x, effects = c("all", "fixed", "random"), ...)

# S3 method for MixMod
get_data(x, effects = c("all", "fixed", "random"),
  component = c("all", "conditional", "zi", "zero_inflated",
  "dispersion"), ...)

# S3 method for brmsfit
get_data(x, effects = c("all", "fixed", "random"),
  component = c("all", "conditional", "zi", "zero_inflated"), ...)

# S3 method for stanreg
get_data(x, effects = c("all", "fixed", "random"), ...)

# S3 method for MCMCglmm
get_data(x, effects = c("all", "fixed", "random"),
  ...)

Arguments

x

A fitted model.

...

Currently not used.

component

Should all predictor variables, predictor variables for the conditional model, the zero-inflated part of the model, the dispersion term or the instrumental variables be returned? Applies to models with zero-inflated and/or dispersion formula, or to models with instrumental variable (so called fixed-effects regressions). May be abbreviated.

effects

Should model data for fixed effects, random effects or both be returned? Only applies to mixed models.

Value

The data that was used to fit the model.

Note

Unlike model.frame(), which may contain transformed variables (e.g. if poly() or scale() was used inside the formula to specify the model), get_data() aims at returning the "original", untransformed data.

Examples

data(cbpp, package = "lme4") cbpp$trials <- cbpp$size - cbpp$incidence m <- glm(cbind(incidence, trials) ~ period, data = cbpp, family = binomial) head(get_data(m))
#> cbind(incidence, trials).incidence cbind(incidence, trials).trials period #> 1 2 12 1 #> 2 3 9 2 #> 3 4 5 3 #> 4 0 5 4 #> 5 3 19 1 #> 6 1 17 2 #> incidence trials #> 1 2 12 #> 2 3 9 #> 3 4 5 #> 4 0 5 #> 5 3 19 #> 6 1 17