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Broom Integration

Source: R/generics_augment.R, R/generics_glance.R, R/generics_tidy.R
broom.Rd

The provided broom methods do the following:

  1. augment: Takes the input data and adds additional columns with the fitted values and residuals.

  2. glance: Extracts the deviance, null deviance, and the number of observations.`

  3. tidy: Extracts the estimated coefficients and their standard errors.

Usage

# S3 method for class 'feglm'
augment(x, newdata = NULL, ...)

# S3 method for class 'felm'
augment(x, newdata = NULL, ...)

# S3 method for class 'feglm'
glance(x, ...)

# S3 method for class 'felm'
glance(x, ...)

# S3 method for class 'feglm'
tidy(x, conf_int = FALSE, conf_level = 0.95, ...)

# S3 method for class 'felm'
tidy(x, conf_int = FALSE, conf_level = 0.95, ...)

Arguments

x

A fitted model object.

newdata

Optional argument to use data different from the data used to fit the model.

...

Additional arguments passed to the method.

conf_int

Logical indicating whether to include the confidence interval.

conf_level

The confidence level for the confidence interval.

Value

A tibble with the respective information for the augment, glance, and tidy methods.

Examples

set.seed(123)
trade_2006 <- trade_panel[trade_panel$year == 2006, ]
trade_2006 <- trade_2006[sample(nrow(trade_2006), 500), ]

mod <- fepoisson(
  trade ~ log_dist + lang + cntg + clny | exp_year + imp_year,
  trade_2006
)

broom::augment(mod)
#> Registered S3 methods overwritten by 'broom':
#>   method       from    
#>   augment.felm capybara
#>   glance.felm  capybara
#>   tidy.felm    capybara
#> # A tibble: 500 × 9
#>      trade log_dist  lang  cntg  clny exp_year imp_year   .fitted .residuals
#>      <dbl>    <dbl> <int> <int> <int> <fct>    <fct>        <dbl>      <dbl>
#>  1  599.       9.00     0     0     0 KOR2006  CYP2006   467.       132.    
#>  2   97.6      9.18     0     0     0 KOR2006  TUN2006   156.       -58.5   
#>  3    4.16     8.80     0     0     0 ITA2006  NPL2006     5.77      -1.61  
#>  4 1609.       8.69     0     0     0 CAN2006  NOR2006  1076.       532.    
#>  5   73.5      9.03     0     0     0 TUN2006  BRA2006    51.5       22.0   
#>  6    0        9.68     0     0     0 MMR2006  TTO2006     0.0899    -0.0899
#>  7   11.0      9.69     0     0     0 IND2006  BOL2006    14.1       -3.09  
#>  8 1454.       6.55     0     0     0 DNK2006  POL2006  1436.        18.3   
#>  9   63.7      9.03     0     0     0 NLD2006  LKA2006   203.      -140.    
#> 10    3.43     9.06     0     0     0 NOR2006  MWI2006     0.583      2.84  
#> # ℹ 490 more rows
broom::glance(mod)
#> # A tibble: 1 × 6
#>   deviance null_deviance nobs_full nobs_na nobs_pc  nobs
#> *    <dbl>         <dbl>     <int>   <int>   <int> <int>
#> 1   55601.      2890992.       500       0       0   500
broom::tidy(mod)
#> # A tibble: 4 × 4
#>   estimate std.error statistic    p.value
#> *    <dbl>     <dbl>     <dbl>      <dbl>
#> 1  -0.794    0.00490   -162.   0         
#> 2   0.0491   0.0103       4.78 0.00000175
#> 3   0.691    0.0113      61.3  0         
#> 4  -0.0239   0.0109      -2.19 0.0287