fs_truthTable: Construction of truthTable from fuzzy set score
In Ronggui/QCA3: Yet Another Package for Qualitative Comparative Analysis

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

Constructing a truthTable from fuzzy set score.

fs_truthTable(mydata, outcome, conditions, ncases_cutoff = 1,
              consistency_cutoff = 0.8, prop_cutoff=1, 
              show.cases =TRUE,quiet = FALSE,
              cases = NULL, complete=FALSE,...)

## S3 method for class 'fs_truthTable'
sort(x, decreasing = TRUE, criterion = "Consistency", ...)

`mydata`	A fuzzy set score dataset. All the scores must range from 0 to 1.
`outcome`	character, the name of the outcome variable in the dataset.
`conditions`	character vetor, the name of the conditions from the dataset.
`ncases_cutoff`	When number of case is less than cutoff, it will be regarded as dontcare configuration.
`consistency_cutoff`	Cutoff point of consistenty score, cases with consistency score greater than cutoff point are regarded as OUT=1.
`prop_cutoff`	proportion of consistent/inconsistent cases.
`show.cases`	show the rownames from the original dataset for each combination of conditions.
`quiet`	Not used currently.
`cases`	character, variable of case names. If it is NULL and show.cases is TRUE, name of cases are derived from row names of dataset.
`complete`	show logical remainders when TRUE.
`...`	Not used currently.
`x`	an fs_truthTable object.
`decreasing`	same as that of sort.
`criterion`	a name from the truthTable, sort the fs_truthTable according to this variable.

There are serveral pillars which make it possible to construct a crip truthTable summarizing the raw data. There is a correspondance between vector space corners and truthTable rows. Thus, it is possible to get the number of cases with strong membership in each corner (usually greater then 0.5), and the consistency of the empirical evidence for each corner. By specifying the frequency thresholds for fuzzy-set assessments (the ncases_cutoff argument), and assessing the consistency of fuzzy-set subset relations (the consistency_cutoff argument), we can finally construct a truthTable.

This function can also be used for crip set QCA as fsQCA software does, though cs_truthTable is specific to csQCA.

There is a sort method and a consistGaps method for the fs_truthTable object.

An object of class "fs_truthTable" and "truthTable".

Ronggui HUANG

Ragin. Charles. 2009. Qualitative Comparative Analyais Using Fuzzy Sets (fsQCA). In Configuraional comparative Methods: qualitative comparative analysis (QCA) and related techniques. ed by Benoit RiHoux and Charles Ragin. Sage. This chapter can be downloaded from http://www.u.arizona.edu/~cragin/fsQCA/software.shtml.

Rubinson, C. (2013), 'Contradictions in fsQCA', Qual Quant 47(5), 2847-2867.

reduce, cs_truthTable and fs_truthTable

fs_truthTable(Lipset_fs,"Survived.FZ",
             c("Developed.FZ","Urban.FZ","Literate.FZ","Industrial.FZ", "Stable.FZ"),
             cases="Country",consistency_cutoff=0.7)

fst <- fs_truthTable(Lipset_fs,"Survived.FZ",
             c("Developed.FZ","Urban.FZ","Literate.FZ","Industrial.FZ", "Stable.FZ"),
             cases="Country",consistency_cutoff=0.7,complete=TRUE)

sort(sort(fst),criterion="OUT")

consistGap(fst)