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A general condition for avoiding effect reversal after marginalization
Author(s) -
Cox D. R.,
Wermuth Nanny
Publication year - 2003
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/1467-9868.00424
Subject(s) - independence (probability theory) , variable (mathematics) , monotonic function , econometrics , conditional independence , mathematics , variables , relation (database) , statistics , computer science , mathematical analysis , database
Summary. The paper examines the effect of marginalizing over a possibly unobserved background variable on the conditional relation between a response and an explanatory variable. In particular it is shown that some conclusions derived from least squares regression theory apply in general to testing independence for arbitrary distributions. It is also shown that the general condition of independence of the explanatory variable and the background ensures that mono‐ tonicity of dependence is preserved after marginalization. Relations with effect reversal and with collapsibility are sketched.