SetMethods (version 2.4)

cases.suf.dcv: List cases deviant with regards to coverage for sufficiency.

Description

A function that extracts cases deviant with regards to coverage for sufficiency from an object of class "qca".

Usage

cases.suf.dcv(results, outcome, neg.out=FALSE, sol = 1)

Arguments

results

An object of class "qca".

outcome

A character string with the name of the outcome in capital letters. When performing pimdata of the sufficient solution for the negated outcome one must only use the minimize() result from the sufficiency analysis of the negated outcome in the argument results. Changing the name in the argument outcome or using a tilde is not necessary.

neg.out

Logical. Should the negated outcome be used?

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.

References

Schneider, C. Q., Rohlfing, I. 2013. Combining QCA and Process Tracing in Set-Theoretic Multi-Method Research. Sociological Methods and Research 42(4): 559-97

See Also

minimize

Examples

# NOT RUN {
# Import your data. For example:

data(SCHF)

# Get the parsimonious solution:


sol_yp <- minimize(SCHF, outcome = "EXPORT",
                conditions = c("EMP","BARGAIN","UNI","OCCUP","STOCK", "MA"),
                incl.cut = .9, 
                include = "?", 					   
                details = TRUE, show.cases = TRUE)

# Get the intermediate solution:

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

# Return deviant cases coverage for sufficiency for the parsimonious solution:

cases.suf.dcv(results = sol_yp, outcome = "EXPORT")

# Return deviant cases coverage for sufficiency for the intermediate solution:

cases.suf.dcv(results = sol_yi, outcome = "EXPORT")

# Get the parsimonious solution for the absence of the outcome:

sol_nyp <- minimize(SCHF, outcome = "EXPORT", neg.out = TRUE,
                conditions = c("EMP","BARGAIN","UNI","OCCUP","STOCK", "MA"),
                incl.cut = .9, 
                include = "?", 					   
                details = TRUE, show.cases = TRUE)

# Return deviant cases coverage for sufficiency for the second parsimonious solution 
# for the absence of the outcome:

cases.suf.dcv(results = sol_nyp, outcome = "EXPORT", neg.out = TRUE, sol = 2)
# }