Some special types of contingency table

1977 ◽  
pp. 108-117
Author(s):  
B. S. Everitt
Keyword(s):  
Contingency Table

scholarly journals A new method for identifying the role of marital preferences at shaping marriage patterns

2021 ◽  
pp. 1-27
Author(s):  
Anna Naszodi ◽  
Francisco Mendonca
Keyword(s):  
Contingency Table ◽  
Transformation Method ◽  
New Method ◽  
Marriage Patterns ◽  
The Us ◽  
Analytical Properties ◽  
The Matrix ◽  
Transformation Methods

Abstract We develop a method which assumes that marital preferences are characterized either by the scalar-valued measure proposed by Liu and Lu, or by the matrix-valued generalized Liu–Lu measure. The new method transforms an observed contingency table into a counterfactual table while preserving its (generalized) Liu–Lu value. After exploring some analytical properties of the new method, we illustrate its application by decomposing changes in the prevalence of homogamy in the US between 1980 and 2010. We perform this decomposition with two alternative transformation methods as well where both methods capture preferences differently from Liu and Lu. Finally, we use survey evidence to support our claim that out of the three considered methods, the new transformation method is the most suitable for identifying the role of marital preferences at shaping marriage patterns. These data are also in favor of measuring assortativity in preferences à la Liu and Lu.

Contingency Table

2018 ◽  
pp. 949-949
Author(s):  
Christian Schutte ◽  
Bradley N. Axelrod
Keyword(s):  
Contingency Table

scholarly journals A Sketch Algorithm for Estimating Two-Way and Multi-Way Associations

2007 ◽  
Vol 33 (3) ◽  
pp. 305-354 ◽  
Author(s):  
Ping Li ◽  
Kenneth W. Church
Keyword(s):  
Contingency Table ◽  
Small Sample ◽  
Entire Population ◽  
The Web

We should not have to look at the entire corpus (e.g., the Web) to know if two (or more) words are strongly associated or not. One can often obtain estimates of associations from a small sample. We develop a sketch-based algorithm that constructs a contingency table for a sample. One can estimate the contingency table for the entire population using straightforward scaling. However, one can do better by taking advantage of the margins (also known as document frequencies). The proposed method cuts the errors roughly in half over Broder's sketches.

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