wop_inter: Calculation of weight of partitions in pooled solution...

Description Usage Arguments Value Examples

View source: R/wop_inter.R

Description

wop_inter calculates the weight of partitions in the pooled solution parameters (consistency, coverage) for the intermediate solution.

Usage

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wop_inter(
  dataset,
  units,
  time,
  cond,
  out,
  n_cut,
  incl_cut,
  intermediate,
  amb_selector
)

Arguments

dataset

Calibrated pooled dataset for partitioning and minimization

units

Units defining the within-dimension of data (time series)

time

Periods defining the between-dimension of data (cross sections)

cond

Conditions used for the pooled analysis

out

Outcome used for the pooled analysis

n_cut

Frequency cut-off for designating truth table rows as observed

incl_cut

Inclusion cut-off for designating truth table rows as consistent

intermediate

A vector of directional expectations to derive the intermediate solutions

amb_selector

Numerical value for selecting a single model in the presence of model ambiguity. Models are numbered according to their order produced by minimize by the QCA package.

Value

A dataframe with information about the weight of the partitions for pooled consistency and coverage scores and the following columns:

Examples

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QCAcluster documentation built on Oct. 26, 2021, 5:06 p.m.