Summarize a POEMED Table

For a grouped table that compares the benchmark and power-enhanced tests (any poemed_tbl with a group column, a pval_hdmm column, and a power-enhanced p-value column (pval_pe or pval_pe_bonferroni), such as the output of WHO_mediation_analysis()), summary() digests it across groups: how many groups each test detects mediation in, and in particular the groups where the power-enhanced test detects mediation that the benchmark misses, together with the most frequently flagged mediators. For any other poemed_tbl it falls back to the ordinary data-frame summary.

Usage

# S3 method for class 'poemed_tbl'
summary(object, alpha_level = 0.05, ...)

# S3 method for class 'summary.poemed_tbl'
print(x, ...)

Arguments

object

A poemed_tbl.

alpha_level

Significance level for counting a group as a detection. Default 0.05.

...

For a grouped comparison table, ignored. For any other poemed_tbl, passed to summary.data.frame() (for example digits or quantile.type).

x

A summary.poemed_tbl object, for the print method.

Value

For a grouped comparison table, an object of class summary.poemed_tbl (a list, printed by its own method) with elements outcome (the outcome label, or NULL when the table has none), full_table (logical; TRUE for the extended layout of WHO_mediation_analysis() with full_table = TRUE), alpha_level, n_groups (rows in the table), n_with_data (groups with a benchmark p-value), n_hdmm and n_pe (groups detected by each test), pe_only (a data.frame of the groups the PE test detects but the benchmark does not, with their n_countries, both p-values, and the active_mediators codes), and top_mediators (a frequency table of the mediators identified as active in the groups the PE test detects). For any other poemed_tbl, the value of summary.data.frame(). The print method returns its argument invisibly.

Details

The printed digest follows the display convention of print.poemed_tbl(): p-values appear to four decimal places, with a < 0.0001 floor and never in scientific notation, and the significance level appears as supplied. The returned object keeps the p-values at full precision.

See also

WHO_mediation_analysis(), pe_mediation().

Other mediation tests: pe_mediate(), pe_mediation(), pe_mediation_linear(), pe_mediation_logistic(), pe_mediation_poisson(), pe_mediators(), pe_selection()

Author

Xiufan Yu and Ken Kelley

Examples

# The global and income-group infant-mortality models, on a 25-point
# version of the default 100-point grid to keep the example fast (the
# global model's grid defaults to the same grid). On the coarser grid
# the screen identifies the same active mediators as on the default grid,
# those of the article's Table 1, and some benchmark p-values move
# slightly.
res <- WHO_mediation_analysis("imr", groupings = c("global", "income"),
                              lambda_grid = seq(0.1, 2, length.out = 25))
summary(res)
#> POEMED comparison: IMR
#>   groups: 5 (5 with data), alpha_level = 0.05
#>   detected by benchmark (HDMM): 1   by power-enhanced (PE): 3
#>   PE detects mediation in 2 groups the benchmark misses:
#>  group n_countries pval_hdmm  pval_pe active_mediators
#>    ALL          91    0.0644 < 0.0001          gge_gdp
#>    Low          16    0.3089 < 0.0001     pvtd_usd2021
#>   most-flagged mediators:
#>     gge_gdp            1
#>     oops_che           1
#>     pvtd_usd2021       1
#>     shi_che            1