theory.evaluation: Membership of cases in the intersections between theory and...

Description Usage Arguments Value Author(s) References See Also Examples

Description

Function that returns membership of cases in the intersections between theory and the empirical solution in the form of a data frame.

Usage

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theory.evaluation(theory, empirics, outcome, intermed=FALSE, sol = 1)

Arguments

theory

A character string specifying the theory. Conditions should be capitalized and negated conditions should be inserted with a "~". Unions of conditions are performed with a "+", while intersections are performed with a "*".

empirics

An object of class 'qca'.

outcome

A character string with the name of the outcome.

intermed

Logical. Use the intermediate solution?

sol

A numeric vector where the first number indicates the number of the solution in case of model ambiguity according to the order in the "qca" object.

Value

It returns a data frame containing the intersections between theory and empirical findings.

Author(s)

Ioana-Elena Oana and Juraj Medzihorsky

References

Ragin, C. C. 1987. The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. Berkeley: University of California Press, pp. 118-121

Schneider, C. Q., Wagemann, C. 2012. Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, chapter 11.3

See Also

eqmcc

Examples

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# Import your data. For example:

data(Schneider)

# Get the intermediate solution:

sol_yi <- eqmcc(Schneider, outcome = "EXPORT",
                conditions = c("EMP","BARGAIN","UNI","OCCUP","STOCK", "MA"),
                incl.cut1 = .9, 
                include = "?", 					   
                details = TRUE, show.cases = TRUE, dir.exp = c(0,0,0,0,0,0))


# Specify the theory. Let's assume the theory says that the 
# absence of EMP and the presence of MA is sufficient for EXPORT:

t<-"~EMP*MA"

# Get membership of cases in the intersections between theory and 
# the second intermediate solution:

theory.evaluation(theory = t, empirics = sol_yi, outcome = "EXPORT", intermed = TRUE, sol = 2)


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