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Estimate weekday sample effects

Source: R/model_sampling.R
sample_effects_estimate_weekday.Rd

This option uses a log-linear regression model to estimate sample weekday effects on the concentration. Concentrations can be influenced by the time between sampling and shipping to the lab (age-of-sample effect), and if shipment follows a weekly batch scheme, the sampling weekday is a good proxy for the age at shipment.

Usage

sample_effects_estimate_weekday(
  effect_prior_mu = 0,
  effect_prior_sigma = 1,
  modeldata = modeldata_init()
)

Arguments

effect_prior_mu

Prior (mean) on the regression coefficients.

effect_prior_sigma

Prior (standard deviation) on the regression coefficients.

modeldata

A modeldata object to which the above model specifications should be added. Default is an empty model given by modeldata_init(). Can also be an already partly specified model returned by other EpiSewer modeling functions.

Value

A modeldata object containing data and specifications of the model to be fitted. Can be passed on to other EpiSewer modeling functions to add further data and model specifications.

The modeldata object also includes information about parameter initialization (init), meta data (.metainfo), and checks to be performed before model fitting (.checks).

Details

Effects are estimated for weekdays Monday - Saturday, with Sunday as the baseline. EpiSewer will fit a fixed-effects log-linear model, random effects are currently not supported.

The priors of this component have the following functional form:

  • regression coefficients: Normal

See also

Other sample effect models: sample_effects_estimate_matrix(), sample_effects_none()