Generates an ENA model by constructing a dimensional reduction of adjacency (co-occurrence) vectors as defined by the supplied conversations, units, and codes.
ena.set.creator(
data,
codes,
units,
conversation,
metadata = NULL,
model = c("EndPoint", "AccumulatedTrajectory", "SeparateTrajectory"),
weight.by = "binary",
window = c("MovingStanzaWindow", "Conversation"),
window.size.back = 1,
include.meta = TRUE,
groupVar = NULL,
groups = NULL,
runTest = FALSE,
...
)ena.set object
data.frame with containing metadata and coded columns
vector, numeric or character, of columns with codes
vector, numeric or character, of columns representing units
vector, numeric or character, of columns to segment conversations by
vector, numeric or character, of columns with additional meta information for units
character: EndPoint (default), AccumulatedTrajectory, SeparateTrajectory
"binary" is default, can supply a function to call (e.g. sum)
MovingStanzaWindow (default) or Conversation
Number of lines in the stanza window (default: 1)
[TBD]
vector, character, of column name containing group identifiers. If column contains at least two unique values, will generate model using a means rotation (a dimensional reduction maximizing the variance between the means of the two groups)
vector, character, of values of groupVar column used for means rotation or statistical tests
logical, TRUE will run a Student's t-Test and a Wilcoxon test for groups defined by the groups argument
Additional parameters passed to model generation
This function generates an ena.set object given a data.frame, units, conversations, and codes. After accumulating the adjacency (co-occurrence) vectors, computes a dimensional reduction (projection), and calculates node positions in the projected ENA space. Returns location of the units in the projected space, as well as locations for node positions, and normalized adjacency (co-occurrence) vectors to construct network graphs. Includes options for returning statistical tests between groups of units.