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

baQCA(mod, sim = 2000, include = c(""), row.dom = F, 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 F.
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

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 <- minimize(truth,details=TRUE,show.cases=TRUE)
mod1

baQCA(mod1,sim=5) 

braQCA documentation built on Feb. 22, 2018, 1:02 a.m.