Polynomial models — polynomial_model • serosv

Either `status` (treated as line-listing dataset) or `pos` & `tot` (treated as aggregated dataset) must be provided

Usage

polynomial_model(
  age,
  k,
  type,
  pos = NULL,
  tot = NULL,
  status = NULL,
  link = "log"
)

Arguments

age: the age vector.
k: degree of the model.
type: name of method (Muench, Giffith, Grenfell).
pos: the positive count vector (optional if status is provided).
tot: the total count vector (optional if status is provided).
status: the serostatus vector (optional if pos & tot are provided).
link: link function.

Value

a list of class polynomial_model with 5 items

datatype: type of datatype used for model fitting (aggregated or linelisting)
df: the dataframe used for fitting the model
info: fitted "glm" object
sp: seroprevalence
foi: force of infection

Details

Refers to section 6.1.1

Examples

data <- parvob19_fi_1997_1998[order(parvob19_fi_1997_1998$age), ]
aggregated <- transform_data(data$age, data$seropositive)

# fit with aggregated data
model <- polynomial_model(aggregated$t, pos = aggregated$pos, tot = aggregated$tot, type = "Muench")
# fit with linelisting data
model <- polynomial_model(data$age, status = data$seropositive, type = "Muench")
plot(model)