Graphical Markov Models: Overview
Kapitel i bok, 2015

We describe how graphical Markov models emerged in the past 40. years, based on three essential concepts that had been developed independently more than a century ago. Sequences of joint or single regressions and their regression graphs are singled out as being the subclass that is best suited for analyzing longitudinal data and for tracing developmental pathways, both in observational and in intervention studies. Interpretations are illustrated using two sets of data. Furthermore, some of the more recent, important results for sequences of regressions are summarized.

Markov equivalence

Intervention studies

Issues of causality

Independence-preserving graphs

Observational studies

Direct confounding

Intersection property

Separation criteria

Longitudinal studies

Composition property

Dependence-inducing distributions

Independence-predicting graphs

Indirect confounding

Regression graphs

Conditional independence

Författare

Nanny Wermuth

Johannes Gutenberg-Universität Mainz

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

D. R. Cox

University of Oxford

International Encyclopedia of the Social & Behavioral Sciences: Second Edition

341-350

Ämneskategorier

Mediateknik

Bioinformatik och systembiologi

Sannolikhetsteori och statistik

DOI

10.1016/B978-0-08-097086-8.42048-9

Mer information

Senast uppdaterat

2018-11-20