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Generate Quiz Pairs for "Which Is Riskier?" Game

Source: R/quiz.R
quiz_pairs.Rd

Creates candidate question pairs from common_risks() for use in an interactive risk comparison quiz. Each pair contains two activities with similar micromort values, making the comparison challenging and educational.

Usage

quiz_pairs(
  min_ratio = 1.1,
  max_ratio = 2,
  prefer_cross_category = TRUE,
  seed = NULL,
  difficulty = NULL,
  profile = list()
)

Arguments

min_ratio

Minimum ratio between micromort values in a pair. Values above 1.0 exclude identical-risk pairs that are unanswerable. Default 1.1. Ignored when difficulty is non-NULL.

max_ratio

Maximum ratio between micromort values in a pair. Lower values produce harder questions. Default 2.0. Ignored when difficulty is non-NULL.

prefer_cross_category

If TRUE (default), pairs from different risk categories are prioritised over same-category pairs.

seed

Optional random seed for reproducibility.

difficulty

Optional difficulty level. One of "easy", "medium", "hard", or "mixed". When non-NULL, overrides min_ratio and max_ratio to use the full pool (ratios 1.5–10) and assigns difficulty

based on data-driven terciles:

  • hard: lowest third of ratios (hardest to distinguish)

  • medium: middle third

  • easy: highest third (easiest to distinguish)

  • mixed: samples equally from all three tiers

When NULL (default), the original min_ratio/max_ratio behaviour is preserved and no difficulty column is added.

profile

A named list of condition variables for filtering conditional risks, passed to common_risks(). E.g. list(country = "US") to include country-specific disease mortality in the quiz pool. Default list() uses population-average unconditional risks only.

Value

A tibble with columns:

  • activity_a, micromorts_a, category_a, hedgeable_pct_a, period_a

  • activity_b, micromorts_b, category_b, hedgeable_pct_b, period_b

  • description_a, help_url_a, description_b, help_url_b

  • ratio (max/min of the two micromort values)

  • answer ("a" or "b" — whichever activity is riskier)

  • difficulty (only when difficulty is non-NULL)

Examples

pairs <- quiz_pairs(seed = 42)
head(pairs)
#> # A tibble: 6 × 16
#>   activity_b         activity_a micromorts_a category_a hedgeable_pct_a period_a
#>   <chr>              <chr>             <dbl> <chr>                <dbl> <chr>   
#> 1 Airline pilot (an… Commuting…        0.13  Travel                   0 per trip
#> 2 All US workers ba… Commuting…        0.13  Travel                   0 per trip
#> 3 American football  COVID-19 …       23     COVID-19                 0 11 week…
#> 4 Base jumping (per… Living in…      500     COVID-19                 0 per mon…
#> 5 Bee/wasp sting (g… High-alti…        0.035 Environme…               0 per year
#> 6 COVID-19 infectio… Himalayan…    12000     Mountaine…               0 per exp…
#> # ℹ 10 more variables: micromorts_b <dbl>, category_b <chr>,
#> #   hedgeable_pct_b <dbl>, period_b <chr>, ratio <dbl>, answer <chr>,
#> #   description_a <chr>, help_url_a <chr>, description_b <chr>,
#> #   help_url_b <chr>

# Easy questions (large ratio differences)
easy <- quiz_pairs(difficulty = "easy", seed = 42)
head(easy)
#> # A tibble: 6 × 17
#>   activity_b         activity_a micromorts_a category_a hedgeable_pct_a period_a
#>   <chr>              <chr>             <dbl> <chr>                <dbl> <chr>   
#> 1 Airline pilot (an… COVID-19 …            1 COVID-19                 0 11 week…
#> 2 Airline pilot (an… Walking (…            1 Travel                   0 per trip
#> 3 Airline pilot (an… Living 2 …            1 Environme…               0 per 2 m…
#> 4 All US workers ba… Train (10…            1 Travel                   0 per trip
#> 5 All US workers ba… Walking (…            1 Travel                   0 per trip
#> 6 All US workers ba… Driving (…            1 Travel                   0 per trip
#> # ℹ 11 more variables: micromorts_b <dbl>, category_b <chr>,
#> #   hedgeable_pct_b <dbl>, period_b <chr>, ratio <dbl>, difficulty <chr>,
#> #   answer <chr>, description_a <chr>, help_url_a <chr>, description_b <chr>,
#> #   help_url_b <chr>

# Country-specific quiz with Nigerian disease risk
ng_pairs <- quiz_pairs(profile = list(country = "NG"), seed = 42)
head(ng_pairs)
#> # A tibble: 6 × 16
#>   activity_b         activity_a micromorts_a category_a hedgeable_pct_a period_a
#>   <chr>              <chr>             <dbl> <chr>                <dbl> <chr>   
#> 1 Airline pilot (an… Commuting…        0.13  Travel                   0 per trip
#> 2 All US workers ba… Commuting…        0.13  Travel                   0 per trip
#> 3 American football  COVID-19 …       23     COVID-19                 0 11 week…
#> 4 Base jumping (per… Living in…      500     COVID-19                 0 per mon…
#> 5 Bee/wasp sting (g… High-alti…        0.035 Environme…               0 per year
#> 6 COVID-19 monovale… General a…       10     Medical                  0 per eve…
#> # ℹ 10 more variables: micromorts_b <dbl>, category_b <chr>,
#> #   hedgeable_pct_b <dbl>, period_b <chr>, ratio <dbl>, answer <chr>,
#> #   description_a <chr>, help_url_a <chr>, description_b <chr>,
#> #   help_url_b <chr>