Make table representation of state counts — sankey_table

sankey_table_maker converts timed sankey data at the patient level to summarized counts in a data.frame

sankey_table_maker(
  id_data,
  cohort,
  id_var = "patient_id",
  index_var = "index_date",
  censor_vars = NULL,
  absorbing_vars = NULL,
  none = "None",
  collapse_states = NULL,
  gofl_formula = NULL,
  wide = T
)

Arguments

id_data: List. One element for patient level order data, one element with states found in that data, one element with stages. Returned from sankey_id_data. Pro tip: if you want to reduce number of stages, edit the stages vector.
cohort: Cohort data.
id_var: String. Variable name of the id/grouping variable.
index_var: Date. Indicates cohort_file date or day variable name per subject when event ordering should begin.
censor_vars: Character vector. Variable names in cohort that indicate censoring date/day. If multiple, sankey_list_maker will use the minimum. If weight = FALSE the Sankey will use the names of the vector to label the states shown. If unnamed will group together under "Censored".
absorbing_vars: Named character vector. Variables in cohort that indicate date/day of states that members cannot transition out of. Names of the vector will be names of the states shown in the Sankey.
none: Character. How to label the "empty" state. Default is "None".
collapse_states: How to redefine states if combinations are anticipated. As a named list it allows users to identify how states should be grouped with unique identifiers. As a named vector it assigns a hierarchy in the order that the states appear. Default NULL.
gofl_formula: Formula. How should the Sankey be filtered? Uses gofl to create groupings. Default is NULL. Overall Sankey is always created.
wide: Return as a wide table? Default TRUE.

Value

Data.frame with