Causality : some statistical aspects

By D. R. Cox. 1992

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Citations in the corpus

The Econometrics of Randomized Experiments (2016, methodology): “We also draw on the literature on causal inference, both in experimental and observational settings, Rosenbaum (1995, 2002, 2009), Rubin (2006), Cox (1992), Morgan and Winship (2007), Morton Williams (2010) and Lee (2005), and Imbens and Rubin (2015).”
Causality, mediation and time: a dynamic viewpoint (2012, background): “There is an analogous concept for local independence graphs called δ-separation which was developed by Didelez (2008). This is defined as follows: consider a directed graph and let A, B and C be three disjoint subsets of nodes. We restrict ourselves to the ancestral graph that is generated by A, B a”
Studying Mechanisms To Strengthen Causal Inferences In Quantitative Research (2008, background): “…in which social-science theory suggests a mathematical model of a causal process and statistics provides the tools to estimate this model, not, as is common today, that statistics provides models that social scientists use as ad hoc models of social processes (see also Cox 1992; Goldthorpe 2000).”
Reporting Analyses of Covariance Structures (2000, background): “If necessary and appropriate, aspects of causal inference might be touched on; see Sobel (1994, 1995, 1996) for some first introductions and an overview and Cox (1992) or Cox and Wermuth (1996) for some cautions to be employed.”
Causality: a Statistical View (2004, background): “We now sketch three different notions of causality.”
1. The Scientific Model of Causality (2005, background): “…on a priori models to define the universe of counterfactuals and the mechanisms of selection and the dependence of estimators of causal parameters on a priori, untestable assumptions.2 Cox (1992) appears to accept the provisional nature of causal knowledge (see also Cox and Wermuth 1996).”
Willingness to Pay for Eco‐Certified Refurbished Products: The Effects of Environmental Attitudes and Knowledge (2016, methodology): “First, our analytical approach is based on correlational patterns that can only be a first step toward establishing causality (Cox 1992).”
Instrumental Variables: An Econometrician's Perspective (2014, background): “In fact, the comment by Cox appears to rule out all simultaneous equations models of the type studied by economists. Holland (1988), in comment on structural equation methods in econometrics, writes “why should [this disturbance] be independent of [the instrument]. . . when the very definition of [t”
Teaching Statistical Inference for Causal Effects in Experiments and Observational Studies (2004, unknown): “Also see Cox (1992).”
Using the Propensity Score Method to Estimate Causal Effects (2013, unknown): “Cox (1992) defined a cause as an intervention that brings about a change in the variable of interest, compared with the baseline control model.”
Pathways between socioeconomic status and health: Does health selection or social causation dominate in Europe? (2018, background): “The causal concept behind our approach is “causation as a generative process”, introduced by Cox (1992), and since further developed in sociology (Blossfeld, 2009; Goldthorpe, 2010).”
Using Narrative in Social Research (2005, methodology): “In a very closely focused qualitative study on how at-risk individuals decide to request predictive testing for Huntingdon’s disease, Cox (2003) also moves away from understanding decision making through the framework of rational choice.”