Description Usage Arguments Value Examples

Provides recommendations for consistency score and configurational n thresholds to attain a desired level of confidence in a QCA algorithm application.

1 2 |

`qca.data` |
the QCA data frame. |

`outcome` |
the outcome variable in the QCA data frame of causal conditions; |

`type` |
of QCA application, |

`inclcut` |
range of consistency scores for inclusion. If not specified, this defaults to |

`ncut` |
configurational n levels to simulate. Can be altered to give options for the range of minimum to maximum |

`neg.out` |
[from QCA package] “Logical, use negation of outcome (ignored if data is a truth table object).” Default set to |

`sim` |
number of simulations to run for each combination of parameters. The final number of simulations is |

`verbose` |
prints the system time used to run the simulation and the percent complete. Default set to |

Significance levels reached (.10,.05, .01, .001) when specifying a combination of inclcut, ncut, and neg.out in a QCA model.

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
brQCA(qca.data,outcome="P",ncut=1,sim=1)
``` |

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