Create an aligned-position consensus sequence — create_consensus

Computes a descriptive consensus state at each observed sequence position. The function does not treat the consensus as a behavioural norm and does not infer psychological or causal meaning.

Usage

create_consensus_sequence(
  data,
  sequence_id_col = "sequence_id",
  order_col = "sequence_order",
  state_col = "state",
  group_cols = NULL,
  weight_col = NULL,
  missing_state_policy = c("exclude", "state", "error"),
  missing_state_label = "<MISSING>",
  tie_method = c("first", "last", "missing", "all"),
  state_levels = NULL,
  min_support = 1L
)

Arguments

data: A long-format data frame, a prepared gp3sequences result, or a data frame containing canonical columns.
sequence_id_col, order_col, state_col: Column names defining sequences.
group_cols: Optional columns defining independent consensus groups.
weight_col: Optional non-negative row-weight column.
missing_state_policy: One of "exclude", "state", or "error".
missing_state_label: Label used when missing states are retained.
tie_method: Deterministic tie policy: "first", "last", "missing", or "all".
state_levels: Optional preferred state ordering used for ties.
min_support: Minimum number of contributing sequences at a position.

Value

A data frame of class gp3_consensus_sequence containing group columns, sequence position, consensus state, support counts and weights, agreement proportion, tie count, tied states, and total group sequences.

Examples

sequences <- data.frame(
  sequence_id = rep(c("s1", "s2", "s3", "s4"), each = 4L),
  sequence_order = rep(1:4, times = 4L),
  state = c("A", "B", "C", "D", "A", "B", "C", "C",
            "D", "C", "B", "A", "D", "C", "A", "A"),
  group = rep(c("g1", "g2"), each = 8L),
  stringsAsFactors = FALSE
)
create_consensus_sequence(sequences, group_cols = "group")
#>   group sequence_order consensus_state support_n support_weight agreement tie_n
#> 1    g1              1               A         2              2       1.0     1
#> 2    g1              2               B         2              2       1.0     1
#> 3    g1              3               C         2              2       1.0     1
#> 4    g1              4               C         2              2       0.5     2
#> 5    g2              1               D         2              2       1.0     1
#> 6    g2              2               C         2              2       1.0     1
#> 7    g2              3               A         2              2       0.5     2
#> 8    g2              4               A         2              2       1.0     1
#>   tied_states n_sequences
#> 1           A           2
#> 2           B           2
#> 3           C           2
#> 4       C | D           2
#> 5           D           2
#> 6           C           2
#> 7       A | B           2
#> 8           A           2