its_zero_inflated_poisson: ITS analysis for count outcomes with excess zeros

In Yael-Travis-Lumer/its2es: Interuppted Time Series Analysis and Corresponding Effect Sizes

ITS analysis for count outcomes with excess zeros

Description

its_zero_inflated_poisson fits a zero-inflated Poisson regression model to an ITS, and returns the model, the summary of the model (including the relative risk), and the original data together with the model predictions.

Usage

its_zero_inflated_poisson(
  data,
  form,
  offset_name = NULL,
  time_name,
  intervention_start_ind,
  freq,
  seasonality = FALSE,
  impact_model = "full",
  counterfactual = FALSE,
  print_summary = FALSE
)

Arguments

data	The data frame corresponding to the supplied formula, existing of at least 2 variables: (1) the count outcome, and (2) a vector of time points
form	A formula with the response on the left, followed by the ~ operator, and the covariates on the right, separated by + operators. The formula should not contain an offest term.
offset_name	either a string indicating the name of the offset column in the data, or NULL. Default value is NULL
time_name	A string giving the name of the time variable. The time variable may or may not be supplied as a covariate in the formula
intervention_start_ind	Numeric - a number between 1 and nrow(data)-1 stating the time point of the start of the intervention
freq	A positive integer describing the frequency of the time series.
seasonality	Logical - indicating whether seasonal adjustment via Fourier terms should be used. Default value is FALSE, in which case seasonal adjustment is not considered.
impact_model	A string specifying the assumed impact model. Possible options include "full" corresponding to a model including both a level change and a slope change, "level" corresponding to a model including just a level change, and "slope" corresponding to a model including just a slope change. Default value is "full".
counterfactual	Logical - indicating whether the model-based counterfactual values should also be returned as an additional column in the data. Default value is FALSE, in which case the counterfactual values are not returned.
print_summary	Logical - indicating whethwe the entire model summary should be printed, or just the relevant effect size. Default value is FALSE in which case only the effect size, together with its 95% CI and P-value, are printed.

Value

The function returns a list with three elements: the fitted Poisson regression model, the summary of the model (including the relative risk), and the original data together with the model predictions.

Examples

data <- zero_inflated_sim_data
form <- as.formula("monthly_total ~ time")
intervention_start_ind <- which(data$Year==2020 & data$Month==3)
fit <- its_zero_inflated_poisson(data=data,form=form, time_name = "time",intervention_start_ind=intervention_start_ind, freq=12, seasonality=TRUE, impact_model = "full",counterfactual = TRUE)

Yael-Travis-Lumer/its2es documentation built on Oct. 31, 2022, 8:05 a.m.