baQCA: Boostrapped Assessment

View source: R/baQCA.R

baQCAR Documentation

Boostrapped Assessment

Description

This function performs the the Bootstrapped Assessment for QCA (baQCA) on a given QCA model object.

Usage

baQCA(
  mod,
  sim = 2000,
  all = TRUE,
  include = c(""),
  row.dom = FALSE,
  omit = c(),
  dir.exp = c()
)

Arguments

mod

name of the QCA model object – the minimization of the truth table.

sim

the number of simulations the baQCA function should run. Default set to sim=2000.

all

logical, whether or not causal conditions AND outcome should be resampled (with replacement). Default set to all=TRUE.

include

[from QCA package] “A vector of additional output function values to be included in the minimization.” Default set to include=c("").

row.dom

[from QCA package] “Logical, impose row dominance as constraint on solution to eliminate dominated inessential prime implicants.” Default set to FALSE.

omit

[from QCA package] “A vector of configuration index values or matrix of configurations to be omitted from minimization.” Default set to omit=c().

dir.exp

[from QCA package] “A vector of directional expectations for deriving intermediate solutions.” Default set to dir.exp=c().

Value

This function returns a value which is the probability of a random QCA result (e.g. a result from random data) given the parameters set by the researcher in the model (configurational n threshold, consistency score threshold, etc), and a confidence interval around this value. This value is interpreted similarly to a p-value."

Examples


qca.data <- rallies[,8:13]
rownames(qca.data)<-rownames(rallies)
truth<-QCA::truthTable(qca.data,outcome="P",sort.by="incl",incl.cut1=0.85,n.cut=1,show.cases=TRUE)
mod1 <- QCA::minimize(truth,details=TRUE,show.cases=TRUE)

summary(baQCA(mod1,sim=1))

braQCA documentation built on April 4, 2025, 5:12 a.m.

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