Step 2: Turn States into Sequences

Aligns every subject on the same observed time axis and returns wide sequences plus tidy long data, state distributions, and transitions.

Usage

step2_sequences(
  data,
  id = NULL,
  time = NULL,
  state = NULL,
  state_order = NULL,
  state_colors = NULL,
  time_levels = NULL,
  missing = c("error", "explicit", "keep"),
  missing_label = "Missing"
)

Arguments

data

A vasstra_states object or a data frame containing states.

id

Subject identifier column. Inferred from vasstra_states, attached role metadata, or a common identifier name.

time

Time or ordering column. Inferred from vasstra_states, attached role metadata, or a common time name.

state

State column. Inferred from vasstra_states, or detected as the single categorical non-role column of a plain data frame.

state_order

Optional character vector giving the order the states should appear in every plot. It must list exactly the observed states, rearranged. Defaults to the state factor's levels, or alphabetical order for a character state column.

state_colors

Optional state palette stored on the result and reused by every plot. A named vector (matched by state) or one colour per state in state order. Inherited from a vasstra_states input when not given.

time_levels

Explicit chronological values. Required for character or unordered-factor time when data is a plain data frame.

missing

Structural-gap policy: "error" (default), "explicit" to create a state for missing subject-time cells, or "keep" to preserve NA cells for advanced use.

missing_label

Label used when missing = "explicit".

Value

A vasstra_sequences object with data (wide state sequences), long_data, meta_data, distribution, and transitions.

Examples

states <- data.frame(
  student = rep(1:3, each = 3),
  course = rep(1:3, 3),
  engagement = c("Low", "Average", "High",
                 "Average", "Average", "High",
                 "Low", "Low", "Average")
)
sequences <- step2_sequences(
  states,
  id = "student",
  time = "course",
  state = "engagement"
)
sequences
#> VaSSTra Step 2: States -> Sequences
#>   3 subjects | 3 times | 3 states | 6 transitions