Estimate seroprevalence and foi by combining mixture model and regression — estimate_from_mixture • serosv

Refers to section 11.2 - 11.4

Usage

estimate_from_mixture(
  age,
  antibody_level,
  threshold_status = NULL,
  mixture_model,
  s = "ps",
  sp = 83,
  monotonize = TRUE
)

Arguments

age: - vector of age
antibody_level: - vector of the corresponding raw antibody level
threshold_status: - sero status using threshold approach in line listing (optional, for visualization and comparison only)
mixture_model: - mixture_model object generated by serosv::mixture_model()
s: - smoothing basis used to fit antibody level
sp: - smoothing parameter
monotonize: - whether to monotonize seroprevalence (default to TRUE)

Value

a list of class estimated_from_mixture with the following items

df: the dataframe used for fitting the model
info: a fitted "gam" model for mu(a)
sp: seroprevalence
foi: force of infection
threshold_status: serostatus using threshold method only if provided

See also

[mgcv::gam()] for more information about the fitted gam object