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Create Model Data for Generalized Linear Modeling

create_model_data.Rd

This function generates a dataset containing all the necessary columns for fitting a Generalized Linear Model (GLM) in the context of epidemiological time series analysis. The generated dataset can include components for seasonality, time trends, and baseline adjustments, depending on the specified model type and intervention parameters.

Usage

create_model_data(
  ts_len,
  model = "mean",
  time_trend = TRUE,
  intervention_start = NULL,
  min_timepoints_baseline = 12,
  min_timepoints_trend = 12,
  past_weeks_not_included = 4
)

Arguments

ts_len

integer, specifying the length of the aggregated timeseries of case counts

model

character, default "mean" one of c("mean", "sincos", "FN") specifying which kind of model the glm is fitting. "mean" fits an intercept model, "sincos" a harmonic sincos model, "FN" uses the seasgroups from farrington to fit parameters for seasonality.

time_trend

boolean, default TRUE, when TRUE a timetrend is fitted in the glm describing the expected number of cases.

intervention_start

integer, specifying the rownumber in the aggregated timeseries which corresponds to the intervention date.

min_timepoints_baseline

integer, default 12, this parameter is only used when intervention_date is not NULL, specifying the number of weeks at least needed for fitting a new baseline after the intervention.

min_timepoints_trend

integer, default 12, this parameter is only used when intervention_date is not NULL, specifying the number of weeks at least needed for fitting a new timetrend after the intervention.

past_weeks_not_included

An integer specifying the number of past weeks to exclude from the fitting process. This can be useful for excluding recent data with outbreaks or data that may not be fully reported. Default is `4`.

Value

data.frame containing all columns needed for the glm model. These are columns for the seasonality, time_trend and intercepts. This model data is used to fit the parameters for these coviariates.

Examples

if (FALSE) { # \dontrun{
create_model_data(100)
create_model_data(100, intervention_start = 50)
} # }