rob.fit {SetMethods}

Function returning robustness parameters of fit.

Description

Function returning robustness parameters of fit of the intersections between an initial sufficient solution and various alternative test solutions.

Usage

rob.fit(test_sol, 
              initial_sol, 
              outcome)

Arguments

test_sol

The different alternative solutions created with minimize() and placed in a list using list().

initial_sol

The initial solution created with minimize().

outcome

A character string containing the name of the outcome.

Author(s)

Ioana-Elena Oana

References

Oana, Ioana-Elena, and Carsten Q. Schneider. 2020. Robustness tests in QCA: A fit-oriented and case-oriented perspective using R. Unpublished Manuscript.

Oana, Ioana-Elena, Carsten Q. Schneider, and Eva Thomann (forthcoming). Qualitative Comparative Analysis (QCA) using R: A Gentle Introduction. Cambridge: Cambridge University Press.

Examples

# Load the data:
data(PAYF)

# Store the name of the conditions in one vector:
conds <-  c("HE","GG","AH","HI","HW")

# Create several solutions:

# The initial solution
IS <- minimize(data = PAYF,
                outcome  = "HL",
                conditions = conds,
                incl.cut = 0.87,
                n.cut = 2,
                include = "?",
                details = TRUE, 
                show.cases = TRUE)

# altering consistency
TS1 <- minimize(data = PAYF,
                 outcome  = "HL",
                 conditions = conds,
                 incl.cut = 0.7,
                 n.cut = 2,
                 include = "?",
                 details = TRUE, show.cases = TRUE)

#altering n.cut
TS2 <- minimize(data = PAYF,
                 outcome  = "HL",
                 conditions = conds,
                 incl.cut = 0.87,
                 n.cut = 1,
                 include = "?",
                 details = TRUE, show.cases = TRUE)
                 
# Create the test set in a list:
TS <- list(TS1, TS2)

# Calculate robustness parameters, i.e. the ratio of the parameters
# of fit for the core vis-a-vis for the initial solution:

RF <- rob.fit(test_sol = TS, 
           initial_sol = IS,  
           outcome = "HL")
RF