Print Method for Revision Summary

Print Method for Revision Summary

Usage

# S3 method for class 'revision_summary'
print(x, interpretation = TRUE, digits = 3, ...)

Arguments

x

An object of class revision_summary.

interpretation

Logical. If TRUE, provides interpretation of key statistics. Default is TRUE.

digits

Integer. Number of digits to display. Default is 3.

...

Additional arguments (not used).

Value

The function returns the input x invisibly.

See also

Other revision analysis: diagnose(), diagnose.revision_summary(), get_first_efficient_release(), get_revision_analysis(), print.lst_efficient(), summary.lst_efficient(), summary.revision_summary()

Examples

df <- dplyr::select(
  get_nth_release(
    na.omit(
      tsbox::ts_pc(
        dplyr::filter(reviser::gdp, id == "US")
      )
    ),
    n = 0:3
  ),
  -"pub_date"
)

final_release <- dplyr::select(
  get_nth_release(
    na.omit(
      tsbox::ts_pc(
        dplyr::filter(reviser::gdp, id == "US")
      )
    ),
    n = "latest"
  ),
  -"pub_date"
)

results <- get_revision_analysis(df, final_release, degree = 1)
print(results)
#> 
#> === Revision Analysis Summary ===
#> 
#> # A tibble: 4 × 14
#>   id    release       N `Bias (mean)` `Bias (p-value)` `Bias (robust p-value)`
#>   <chr> <chr>     <dbl>         <dbl>            <dbl>                   <dbl>
#> 1 US    release_0   178         0.023            0.3                     0.255
#> 2 US    release_1   177         0.02             0.347                   0.288
#> 3 US    release_2   176         0.022            0.311                   0.238
#> 4 US    release_3   175         0.032            0.133                   0.053
#> # ℹ 8 more variables: Minimum <dbl>, Maximum <dbl>, `10Q` <dbl>, Median <dbl>,
#> #   `90Q` <dbl>, MAR <dbl>, `Std. Dev.` <dbl>, `Noise/Signal` <dbl>
#> 
#> === Interpretation ===
#> 
#> id=US, release=release_0:
#>   • No significant bias detected (p = 0.255 )
#>   • Moderate revision volatility (Noise/Signal = 0.27 )
#> 
#> id=US, release=release_1:
#>   • No significant bias detected (p = 0.288 )
#>   • Moderate revision volatility (Noise/Signal = 0.257 )
#> 
#> id=US, release=release_2:
#>   • No significant bias detected (p = 0.238 )
#>   • Moderate revision volatility (Noise/Signal = 0.26 )
#> 
#> id=US, release=release_3:
#>   • No significant bias detected (p = 0.053 )
#>   • Moderate revision volatility (Noise/Signal = 0.252 )

# Print without interpretation
print(results, interpretation = FALSE)
#> 
#> === Revision Analysis Summary ===
#> 
#> # A tibble: 4 × 14
#>   id    release       N `Bias (mean)` `Bias (p-value)` `Bias (robust p-value)`
#>   <chr> <chr>     <dbl>         <dbl>            <dbl>                   <dbl>
#> 1 US    release_0   178         0.023            0.3                     0.255
#> 2 US    release_1   177         0.02             0.347                   0.288
#> 3 US    release_2   176         0.022            0.311                   0.238
#> 4 US    release_3   175         0.032            0.133                   0.053
#> # ℹ 8 more variables: Minimum <dbl>, Maximum <dbl>, `10Q` <dbl>, Median <dbl>,
#> #   `90Q` <dbl>, MAR <dbl>, `Std. Dev.` <dbl>, `Noise/Signal` <dbl>