Immunity: Geographic & Age-based Projection, imuGAP

This a sampler interface to convert user-friendly data into the necessary format to feed the immunity estimation model.

Usage

imuGAP(
  observations,
  populations,
  locations,
  imugap_opts = imugap_options(),
  stan_opts = stan_options()
)

Arguments

observations

a [data.frame()], the observed data, with at least three columns:

• an obs_id column; any type, as long as unique, non-NA

• a `positive“ column; non-negative integers, the observed number of vaccinated individuals

• a sample_n column; positive integers, the number of individuals sampled, must be greater than or equal to "positive"

• optionally, a censored column; numeric, NA (uncensored) or 1 (right-censored); if not present, will be assumed NA

populations

a [data.frame()], the the observation meta data, with columns

• obs_id, any type; the observation the row concerns (i.e. id shared with an observations data object)

• `loc_id“, any type; the location the row concerns (i.e. id shared with a locations data object)

• dose, a non-zero, positive integer (1, 2, ...); what dose row concerns

• cohort, a positive integer; the cohort at the location row concerns

• age, a positive integer; the age of that cohort row concerns

• weight, a numeric, (0, 1); the relative contribution of this row to an observation Note that multiple rows may concern the same observation, meaning that the populations from different cohorts, locations, and ages may be pooled in an observation

locations

a [data.frame()], with columns loc_id and parent_id, of the same type. See Details for restrictions.

imugap_opts

options for the imuGAP model

stan_opts

passed to rstan::sampling (e.g. iter, chains).

Value

An object of class stanfit returned by rstan::sampling