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

Description

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

Usage

 1 2 3 4 5 6 7 8 baQCA( mod, sim = 2000, include = c(""), row.dom = FALSE, omit = c(), dir.exp = c() )

Arguments

 mod name of the QCA eqmcc/minimize model object. sim the number of simulations the baQCA function should run. Default set to sim=2000. 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

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."

Examples

 1 2 3 4 5 6 qca.data <- ,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) baQCA(mod1,sim=2)

braQCA documentation built on Jan. 19, 2022, 1:06 a.m.