Entailment analysis
From InterSciWiki
Doug White's entailment analysis and 3-way interaction tests
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[edit] The larger Package: Tools for Latent Discrete Structure Analysis [R]
http://intersci.ss.uci.edu/wiki/drw/ldsa_0.1-2-EntailmentByCarterButts.zip entailment package in R (provisional) Carter Butts (ldsa_0.1-2.zip ldsa_0.1-2.tar.gz)
The current package is alpha ware, but the entailment stuff works. A good place to start vis a vis the help (for the parts which are documented) is sea.table. ----Carter 05:00, 9 January 2008. The whole Latent Discrete Structure Analysis is at http://eclectic.ss.uci.edu/~drwhite/entail/Carter/00Index.html
[edit] Entailment Analysis proper in R (Implemented by Carter Butts)
http://eclectic.ss.uci.edu/~drwhite/entail/Carter/00EntailmentIndex.html
[edit] Doug's 1977 paper with Burton and Brudner 1988 with McCann
http://eclectic.ss.uci.edu/~drwhite/links2pdf.htm#Entailment
[edit] Sexual division of labor
Douglas R. White, Michael L. Burton, and Lilyan A. Brudner 1977 Entailment Theory and Method: A Cross-Cultural Analysis of the Sexual Division of Labor. Cross Cultural Research 12:1-24. These data are from the Standard Cross-Cultural Sample. These gender orderings have been replicated in archaeological studies. Download data in these formats: spss excel
3-way interaction: This test, for binary variables, is used prior to entailment analysis to verify the absence of greater-than-random occurrence of higher-order interactions.
[edit] 2009 IMBS Talk on Entailment Logics
COLLOQUIUM
I. R. GOODMAN Space and Naval Warfare Systems Center and DONALD BAMBER Department of Cognitive Sciences, UCI
“Entailment in Conditional Probability Logics and Its Relation to Conditional Event Algebra”
Thursday, October 15 SSPA 2112 4:00 – 5:00 p.m.
The calculus of probabilities, in addition to being a numeric tool, is a kind of logic; it falls into the category of multi-valued, non-truth-functional logics. However, this logic has its limitations. There is a variety of questions that arise in both everyday reasoning and in science that the probability calculus cannot answer. Some of these questions are explicitly probabilistic, some only implicitly so. For example: If the conditional probability of A given B is 0.8, what is the best estimate of the conditional probability of not-B given not-A? Another example: If nearly all A’s are B’s and nearly all B’s are C’s, should we expect that nearly all A’s are C’s? To answer such questions, new probability logics are needed.
In this talk, we present both general background and specific new results for one branch of probabilistic reasoning, namely, entailment (of conclusions from premises) in conditional probability logics. We also present both old and new significant results in a little-known and underdeveloped field at the juncture of probability theory and algebra – conditional event algebra (CEA). CEA has already proven very useful in both formulating and deriving results in our ongoing efforts in conditional probability logics.
