Pairwise correlation of indicators on the spine

Which indicators move together across countries? Computes pairwise correlations between indicator columns (pairwise-complete, so patchy coverage doesn't shrink every pair to the common subset), with the per-pair n reported so a headline r computed on 12 countries can't masquerade as a world fact.

Usage

correlate_indicators(
  data,
  ...,
  method = c("pearson", "spearman"),
  min_n = 3,
  by_year = FALSE,
  weight = NULL
)

Arguments

data

A country-level (or map-ready) data frame; map-ready frames are reduced to one row per country first, so the reported n counts countries rather than geometry rows.

...

<tidy-select> Indicator columns to correlate. If empty, all numeric columns except coordinates, year and other structural columns are used.

method

"pearson" (default) or "spearman".

min_n

Minimum number of complete pairs for a correlation to be reported (default 3).

by_year

If TRUE, correlate within each year of a panel and return one table per year, stacked with a leading year column. FALSE (default) wants one row per country and, handed a panel, keeps each country's earliest year with a warning.

weight

Optional column (unquoted), typically population, to weight each country by. Unweighted, every country counts once (Milanovic's "concept 1"); weighted by population, a correlation describes the average person rather than the average country ("concept 2"). A Spearman correlation is weighted on the ranks.

Value

A tibble with one row per indicator pair: var_x, var_y, r, n (complete pairs), sorted by |r| descending; with by_year = TRUE, the same per year, led by year.

Examples

correlate_indicators(countryatlas::world_snapshot$countries)
#> # A tibble: 6 × 4
#>   var_x           var_y                  r     n
#>   <chr>           <chr>              <dbl> <int>
#> 1 gdp_per_capita  life_expectancy  0.607     199
#> 2 life_expectancy co2_per_capita   0.307     203
#> 3 gdp_per_capita  co2_per_capita   0.295     191
#> 4 gdp_per_capita  population      -0.0567    199
#> 5 population      life_expectancy -0.0194    216
#> 6 population      co2_per_capita   0.00663   203
# weighted by population: the correlation for the average person
correlate_indicators(countryatlas::world_snapshot$countries,
                     gdp_per_capita, life_expectancy, weight = population)
#> # A tibble: 1 × 4
#>   var_x          var_y               r     n
#>   <chr>          <chr>           <dbl> <int>
#> 1 gdp_per_capita life_expectancy 0.600   199