creates a matrix of the sufficiency and necessity scores for a crisp set or fuzzy set data frame.

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`x` |
For coincide, x is a dataframe of crip set or fuzzy set data, which ranges from 0 to 1. |

`use` |
The method of handling missing data. "complete" means listwise deletion and "pairwise" means pairwise deletion. |

`digits` |
a non-null value for 'digits' specifies the minimum number of significant digits to be printed in values. |

`...` |
arguments passed to default method of print. |

In the terminology of set theory, if X is the sufficient condition of Y, then the score of X should be consistently less or equal than that of Y. Similarly, if X is the necessary condition of Y, then the sore of X should be consistently greater or equal than that of Y. The necessary score measures such consitency. The formulas can be found in Ragin(2006:297).

For crip set, sufficient score measures proportation of Y=1 given that X=1. The neccessary score measures the proportation of X=1 given that Y=1.

A list of two matrixs of consistency score.

`suff` |
Sufficiency Scores Matrix,measuring the consistency score of 'X is sufficient condition of Y'. |

`nec` |
Necessity Scores Matrix, measuring the consistency score of 'X is necessary condition of Y'. |

Ronggui HUANG

Ragin, Charles C. 2006. "Set Relations in Social Research:Evaluating Their Consistency and Coverage." Political Analysis 14 (3) : 291-310

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