baQCA: Boostrapped Assessment
In braQCA: Bootstrapped Robustness Assessment for Qualitative Comparative Analysis

Description Usage Arguments Value Examples

View source: R/baQCA.R

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

1 2	baQCA(mod, sim = 2000, include = c(""), row.dom = F, omit = c(), dir.exp = c())

`mod`	name of the QCA eqmcc model object.
`sim`	the number of simulations the baQCA function should run. Default set to `sim=2000`.
`include`	[from QCAGUI package] “A vector of additional output function values to be included in the minimization.” Default set to `include=c("")`.
`row.dom`	[from QCAGUI package] “Logical, impose row dominance as constraint on solution to eliminate dominated inessential prime implicants.” Default set to `F`.
`omit`	[from QCAGUI package] “A vector of configuration index values or matrix of configurations to be omitted from minimization.” Default set to `omit=c()`.
`dir.exp`	[from QCAGUI package] “A vector of directional expectations for deriving intermediate solutions.” Default set to `dir.exp=c()`.

After some time, this function returns the probability that the data will return a random result given the parameters set by the researcher in the model (configurational n threshold, consistency score threshold, etc), as well a confidence interval around this value. This value is interpreted similarly to a p-value, i.e. a .05 value coincides with a 95% "confidence level."

data(rallies)
P<-rallies$P
R<-rallies$R
C<-rallies$C
U<-rallies$U

qca.data<-data.frame(P,R,C,U)
rownames(qca.data)<-rownames(rallies)
truth<-truthTable(qca.data,outcome="P",sort.by="incl",incl.cut1=0.7,show.cases=TRUE)
truth
mod1 <- eqmcc(truth,details=TRUE,show.cases=TRUE)
mod1

baQCA(mod1,sim=5)