baQCA | R Documentation |
This function performs the the Bootstrapped Assessment for QCA (baQCA) on a given QCA model object.
baQCA(
mod,
sim = 2000,
all = TRUE,
include = c(""),
row.dom = FALSE,
omit = c(),
dir.exp = c()
)
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 |
all |
logical, whether or not causal conditions AND outcome should be resampled (with replacement). Default set to |
include |
[from QCA package] “A vector of additional output function values to be included in the minimization.” Default set to |
row.dom |
[from QCA package] “Logical, impose row dominance as constraint on solution to eliminate dominated inessential prime implicants.” Default set to |
omit |
[from QCA package] “A vector of configuration index values or matrix of configurations to be omitted from minimization.” Default set to |
dir.exp |
[from QCA package] “A vector of directional expectations for deriving intermediate solutions.” Default set to |
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."
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))
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