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actiquantiles maps physical activity values to
NHANES-based quantiles. The package exposes an
acti_-prefixed wrapper around
mapnhanespa::map_nhanes_pa_quantiles() so the public API
can stay stable while new mapping backends are added later.
Core entry points:
acti_map_nhanes() for participant-level quantile
mappingmapnhanespa::nhanes_pa_quantile() for a single value
lookupmapnhanespa::nhanes_pa_age_category() for age
binningYou can install actiquantiles from GitHub with:
# install.packages("remotes")
remotes::install_github("jhuwit/actiquantiles")The package depends on mapnhanespa, which provides the
NHANES mapping tables and lookup logic.
example_data <- data.frame(
id = c("A", "B"),
age = c(25, 62),
sex = c("Female", "Male"),
measure = c("mims", "ssl_steps"),
value = c(15000, 7500)
)
mapped <- acti_map_nhanes(example_data)
mapped
#> id age sex measure value acti_pa_quantile
#> 1 A 25 Female mims 15000 0.5349443
#> 2 B 62 Male ssl_steps 7500 0.3527381The wrapper keeps the input columns and adds
acti_pa_quantile:
head(mapped)
#> id age sex measure value acti_pa_quantile
#> 1 A 25 Female mims 15000 0.5349443
#> 2 B 62 Male ssl_steps 7500 0.3527381For a single value, use the scalar helper from
mapnhanespa directly:
mapnhanespa::nhanes_pa_quantile(
value = 15000,
age = 25,
sex = "Female",
measure = "mims"
)
#> [1] 0.5349443These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.