SetMethods (version 1.0)

QCAfit: Function calculating the parameters of fit

Description

QCAfit is a function calculating parameters of fit useful in QCA and fsQCA that are consistency, coverage, PRI and PRODUCT. It works with both single and multiple conditions.

Usage

QCAfit(x, y, cond.lab = NULL, necessity = FALSE, negation = FALSE)

Arguments

x

is a vector containing the values of a condition or a matrix with more than one conditions.

y

is a vector containing the values of the output.

cond.lab

is a vector containing the label(s) of the condition(s).

necessity

logical. It indicates if the output should be for sufficient or necessary condition(s). By default, TRUE, the function returns a table of parameters of fit for sufficient condition(s) (Consistency, Coverage, PRI and Product). When it set to FALSE the function returns a table of parameters of fit for necessary condition(s) (Consistency, Coverage, Relevance of Necessity).

negation

logical. It indicates if the parameters of fit should be computed for the positive or the negative outcome. By default it is set to be FALSE, so it returns parameters of fit for the positive outcome.

Value

References

Schneider, C. Q., Wagemann, C. (2012) Set-Theoretic Methods for the Social Sciences, Cambridge University Press: Cambridge.

Schneider, C. Q., Wagemann, C., Quaranta, M. (2012) How To... Use Software for Set-Theoretic Analysis. Online Appendix to "Set-Theoretic Methods for the Social Sciences". Available at www.cambridge.org/schneider-wagemann

Examples

# Generate fake data
set.seed(1234)

a <- runif(100, 0, 1)
b <- runif(100, 0, 1)
c <- runif(100, 0, 1)
y <- runif(100, 0, 1)

# Only one condition, for sufficiency
QCAfit(a, y, cond.lab = "A")

# With three conditions, for sufficiency
QCAfit(cbind(a, b, c), y, cond.lab = c("A", "B", "C"))

# Only one condition, for necessity
QCAfit(a, y, cond.lab = "A", necessity = TRUE)

# With three conditions, for necessity
QCAfit(cbind(a, b, c), y, cond.lab = c("A", "B", "C"), necessity = TRUE)

# With three conditions and negated output, for sufficiency
QCAfit(cbind(a, b, c), y, cond.lab = c("A", "B", "C"), negation = TRUE)