Get the estimate table of a fit

get_estimates() returns the table of fixed-effect estimates of a fit, with their standard errors, degrees of freedom and intervals. For a method comparison it returns the table that lines up the estimates of the compared fits.

Usage

get_estimates(x, ...)

# Default S3 method
get_estimates(x, ...)

# S3 method for class 'pvstackr_fit'
get_estimates(x, ...)

# S3 method for class 'pvstackr_method_comparison'
get_estimates(x, ...)

# S3 method for class 'pvstackr_legacy_psis_inspection'
get_estimates(x, ...)

Arguments

x

A fit (class pvstackr_fit) from pv_fit() or a method function, or a method comparison from pv_compare_methods().

...

Ignored.

Value

A data frame with one row per fixed effect. For a stack_direct fit it has 17 columns: term, estimate, se, std.error, df, df_method, df_complete, conf_level, conf_low, conf_high, conf.low, conf.high, interval_role, coverage_claim_allowed, parameter_scope, target_source and target_hash. per_pv and stack_psis fits add further columns. The fraction of missing information is not a column; for stack_direct and per_pv fits it is get_target(fit)$fmi. A blocked fit gives an empty data frame. For a method comparison, the data frame has one row per method and fixed effect (see pv_compare_methods()).

get_estimates() stops with an error if the fit or comparison was changed after it was created, and for the inspection object that pv_migrate_legacy_psis_fit() makes from a stack_psis fit of an earlier pvstackr version, which has no estimates.

Details

Only the fixed effects are reported. coverage_claim_allowed says whether pvstackr's reporting rule lets you read the interval of a row as a confidence interval with nominal coverage; pv_fit() gives the rule, and pvstackr_object_contracts describes every column.

See also

pvstackr_object_contracts for the columns of the estimate table.

Other pvstackr-accessors: get_diagnostics(), get_draws(), get_target()

Examples

path <- system.file(
  "extdata", "examples", "pisa_tiny_stack_direct.rds", package = "pvstackr"
)
if (nzchar(path)) {
  fit <- readRDS(path)$fit
  head(get_estimates(fit))
}
#>          term   estimate        se std.error       df df_method df_complete
#> 1 b_Intercept 457.894088 1.2873118 1.2873118 1.021194   classic          NA
#> 2         b_x  46.883361 0.3717929 0.3717929 1.402308   classic          NA
#> 3    b_female   2.143702 3.5550309 3.5550309 1.013730   classic          NA
#>   conf_level  conf_low conf_high  conf.low conf.high             interval_role
#> 1       0.95 442.31804 473.47013 442.31804 473.47013 descriptive_classic_rubin
#> 2       0.95  44.41457  49.35215  44.41457  49.35215 descriptive_classic_rubin
#> 3       0.95 -41.60687  45.89428 -41.60687  45.89428 descriptive_classic_rubin
#>   coverage_claim_allowed parameter_scope          target_source
#> 1                  FALSE    fixed_effect external_brr_fay_rubin
#> 2                  FALSE    fixed_effect external_brr_fay_rubin
#> 3                  FALSE    fixed_effect external_brr_fay_rubin
#>                                                               target_hash
#> 1 sha256:f173650e9120742a1a6fc6406bfe3ab130e454b17f28e4822cb99e25c108bfaa
#> 2 sha256:f173650e9120742a1a6fc6406bfe3ab130e454b17f28e4822cb99e25c108bfaa
#> 3 sha256:f173650e9120742a1a6fc6406bfe3ab130e454b17f28e4822cb99e25c108bfaa