Related Causal Frameworks for Surrogate Outcomes

By M. Joffe, Tom Greene. 2009

218 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

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Citations in the corpus

External Validity: From Do-Calculus to Transportability Across Populations (2014, methodology): “and generalizing from diverse studies are handled by methods of meta analysis (Glass (1976); Hedges and Olkin (1985); Owen (2009)), or hierarchical models (Gelman and Hill (2007)), in which results of diverse studies are pooled together by standard statistical procedures (e.”
Principal causal effect identification and surrogate end point evaluation by multiple trials (2015, background): “Joffe and Greene (2009) considered four different approaches for evaluating surrogate end points.”
The Causal Foundations of Structural Equation Modeling (2012, background): “…is now standard in epidemiology research (Robins, 2001; Petersen et al., 2006; VanderWeele and Robins, 2007; Hafeman and Schwartz, 2009; Joffe and Green, 2009; VanderWeele, 2009; Kaufman, 2010) and is making its way slowly toward the social and behavioral sciences (Morgan and Winship, 2007; Imai…”
Estimation of direct effects for survival data by using the Aalen additive hazards model (2011, methodology): “…additive hazards scale and estimated by extending the principle of sequential G-estimation for direct effects in linear models (Goetgeluk et al., 2008; Joffe and Greene, 2009; Vansteelandt, 2009), which itself inherits from generic G-estimation methods for structural nested models (Robins, 1997).”
Long-term Causal Inference Under Persistent Confounding via Data Combination (2022, unknown): “The seminal work of Miao et al. [2016] demonstrated the identification of treatment effects with unobserved confounders given two different types of proxy variables: negative control outcomes, which are not affected by the treatment, and negative control treatments, which do not affect the outcome.”
Some Thoughts Concerning Transfer Learning, with Applications to Meta-analysis and Data-sharing Estimation (2012, background): “Putting aside debates on whether good prediction, void of causal mediation is sufficient for the task (see Prentice, 1989; Joffe and Green, 2009; Pearl and Bareinboim, 2011; Pearl, 2011), the problem fits well into the model of Figs.”
Augmented designs to assess principal strata direct effects (2011, background): “Tables 10–12 show the hypothetical full and observed data of the standard randomized experiment, and the corresponding estimated bounds for PSDE(0) and PSDE(1) defined in equation (1). Consistently with the above assumptions, these bounds are similar to those for PSDE.0; e, e/ and PSDE.1; e, e/= PSD”
Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index (2016, background): “Others have noted that unmeasured confounding between the surrogate and long-term outcome would invalidate the statistical surrogacy assumption, even if the treatment had no direct effect on the long-term outcome (Rosenbaum 1984, Frangakis and Rubin 2002, Joffe and Greene 2009, VanderWeele 2015).”