Description Usage Arguments Value Examples

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

1 2 |

`mod` |
name of the QCA eqmcc/minimize model object. |

`sim` |
the number of simulations the baQCA function should run. 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 |

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."

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
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)
``` |

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