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Generates an ENA model by constructing a dimensional reduction of adjacency (co-occurrence) vectors in an ENA data object
ena.make.set(enadata, dimensions = 2, norm.by = sphere_norm_c,
rotation.by = ena.svd, rotation.params = NULL, rotation.set = NULL,
endpoints.only = T, node.position.method = lws.positions.sq, ...)
ENAdata
that will be used to generate an ENA model
The number of dimensions to include in the dimensional reduction
A function to be used to normalize adjacency (co-occurrence) vectors before computing the dimensional reduction, default: sphere_norm_c()
A function to be used to compute the dimensional reduction, default: ena.svd()
(optional) A character vector containing additional parameters for the function in rotation.by, if needed
A previously-constructed ENARotationSet object to use for the dimensional reduction
A logical variable which determines whether to only show endpoints for trajectory models
A function to be used to determine node positions based on the dimensional reduction, default: lws.position.es()
additional parameters addressed in inner function
ENAset
class object that can be further processed for analysis or plotting
This function generates an ENAset object from an ENAdata object. Takes the adjacency (co-occurrence) vectors from enadata, 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
# NOT RUN {
data(RS.data)
codeNames = c('Data','Technical.Constraints','Performance.Parameters',
'Client.and.Consultant.Requests','Design.Reasoning','Collaboration');
accum = ena.accumulate.data(
units = RS.data[,c("UserName","Condition")],
conversation = RS.data[,c("Condition","GroupName")],
metadata = RS.data[,c("CONFIDENCE.Change","CONFIDENCE.Pre","CONFIDENCE.Post")],
codes = RS.data[,codeNames],
window.size.back = 4
)
set = ena.make.set(
enadata = accum
)
set.means.rotated = ena.make.set(
enadata = accum,
rotation.by = ena.rotate.by.mean,
rotation.params = list(
accum$metadata$Condition=="FirstGame",
accum$metadata$Condition=="SecondGame"
)
)
# }
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