QCA.random: QCA Sufficiency Inclusion Score & Minimum Frequency Threshold...

In jmedzihorsky/qca.sim: qca.sim

Description

Returns QCA results for a range of minimum frequency thresholds across an arbitrarily large set of sufficiency inclusion scores when a random variable is repeatedly added to the dataset

Usage

QCA.random(n, type, data, outcome, conditions=NULL, 
    min.incl.cut, max.incl.cut, min.n.cut, 
    max.n.cut, reps, plot, plot.legend, ...)

Arguments

n	number of times to simulate random variable inclusion
type	type of random variabe to be included; either "binary", which samples from 0 and 1, or "uniform", which draws from a uniform distribution bound by 0 and 1
data	an object of class 'data.frame'
outcome	a character string or column index indicating the outcome variable
conditions	optional character vector or vector of column indices indicating explanatory variables
min.incl.cut	numeric lower bound for sampling of sufficiency inclusion scores
max.incl.cut	numeric upper bound for sampling of sufficiency inclusion scores
min.n.cut	numeric lower bound for minimum frequency thresholds
max.n.cut	numeric upper bound for minimum frequency thresholds
reps	number of sufficiency inclusion score pairs to be sampled
plot	if TRUE, plot solutions
plot.legend	"solutions" indicates plot legend should contain actual unique solutions; "ids" indicates plot should contain numeric identifiers for unique solutions; "none" indicates plot should not contain a legend
...	optional arguments passed to eqmcc()

Value

plot	plot of QCA results for given sufficiency inclusion score pairs and minimum frequency thresholds
results	data frame containing combinations of sufficiency inclusion scores and QCA solutions
legend	list containing unique solutions (config) and their numeric identifiers (config.id)

Author(s)

Chris Krogslund, http://ckro.gs; [e-mail]

Examples

protest.data<-read.csv(file="http://philhoward.org/wp-content/
    uploads/2012/11/International-Studies-Review-Replication-Data.csv")
protest.data<-protest.data[,!colnames(protest.data) 

QCA.random(n=3, type="uniform", data=protest.data, outcome="success", 
    min.incl.cut=0, max.incl.cut=1, min.n.cut=1, 
    max.n.cut=4, reps=100, plot=TRUE, plot.legend="ids")
    
QCA.random(n=5, type="uniform", data=protest.data, outcome="success", 
    conditions=c("mobile", "fuel"), min.incl.cut=0, 
    max.incl.cut=1, min.n.cut=1, max.n.cut=4, reps=100, 
    plot=TRUE, plot.legend="ids")

jmedzihorsky/qca.sim documentation built on May 19, 2019, 1:53 p.m.