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Generate cross-domain quiz pairs comparing acute and chronic risks

Source: R/combined_quiz.R
combined_quiz_pairs.Rd

Creates candidate question pairs mixing acute risks from common_risks() (micromorts per event) with chronic risks from chronic_risks() (microlives per day), converting both to a common microlife scale so they can be directly compared. Each pair pits one acute activity against one chronic lifestyle factor and asks which has a larger total impact over time_period_days.

Usage

combined_quiz_pairs(n = 10, time_period_days = 365, seed = NULL)

Arguments

n

Integer. Number of pairs to generate. Default 10.

time_period_days

Numeric. Time period for chronic risk accumulation. Default 365 (1 year). For chronic risks, the cumulative impact is abs(microlives_per_day) × time_period_days.

seed

Integer or NULL. Random seed for reproducibility. Default NULL (random each call). Acute risks with period_type == "event" (true one-off events such as one expedition or one base jump) keep their raw micromort value. Acute risks with period type day/hour/month/year represent a repeatable rate of exposure and are projected to time_period_days via micromorts_per_day_raw × time_period_days before conversion to microlives. period_type == "period" rows are split by their period string: a plain "N weeks (YEAR)" surveillance-rate phrasing (e.g. "11 weeks (2022)") scales the same as day/hour/month/year, while a "per N weeks"/"per N months" bounded-window phrasing (e.g. "per 8 weeks" for a specific historical interval) keeps its raw micromort value like an event row. The unrounded column (micromorts_per_day_raw) is used rather than the display-rounded micromorts_per_day to prevent low-rate annual/monthly rows from collapsing to zero after rounding (e.g. 0.003 µm/day rounds to 0.00).

Value

A tibble with columns:

  • activity_a, type_a ("acute"), value_a (raw micromorts as stored), unit_a ("micromorts"), category_a, period_a, period_type_a (one of "event", "day", "hour", "month", "year", "period"), effective_micromorts_a (raw value for "event" rows and bounded-window "period" rows; micromorts_per_day_raw × time_period_days otherwise)

  • factor_b, type_b ("chronic"), value_b, unit_b ("microlives/day"), category_b, direction_b

  • common_unit ("microlives"), common_value_a (effective_micromorts_a × 0.7), common_value_b

  • correct_answer ("a" or "b" — whichever has higher impact in common unit)

  • ratio (larger / smaller common value)

  • explanation describing both values and the conversion

Details

The conversion from micromorts to microlives uses the factor 0.7 (1 micromort ≈ 0.7 microlives at age 40). Chronic impact over the time period is abs(microlives_per_day) × time_period_days.

Examples

pairs <- combined_quiz_pairs(n = 5, seed = 42)
pairs[, c("activity_a", "factor_b", "correct_answer", "ratio")]
#> # A tibble: 5 × 4
#>   activity_a                              factor_b          correct_answer ratio
#>   <chr>                                   <chr>             <chr>          <dbl>
#> 1 Matterhorn ascent                       Average cancer d… b               1.10
#> 2 Logging (per work day)                  Sitting 8+ hours… a               1.16
#> 3 Logging (per work day)                  4th-5th alcoholi… a               1.16
#> 4 Spanish flu infection                   Smoking 10 cigar… a               1.15
#> 5 Living in US during COVID-19 (Jul 2020) Smoking 20 cigar… a               1.17

# One year time period (default)
pairs_year <- combined_quiz_pairs(n = 10, time_period_days = 365, seed = 1)