Targeted Learning in Data Science. Causal Inference for Complex Longitudinal Studies.

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Artificial Intelligence in Human Resources Management: Challenges and a Path Forward (2019, background): “Targeted learning 52 is one methodological approach that combines correlations-based pattern recognition with the subsequent targeted estimation of causal parameters and thus delivers a larger scope of benefits: more accurate predictions, generalizability, explain-ability, and fairness.”
Nonparametric efficient causal mediation with intermediate confounders (2019, methodology): “…EIF as an estimating equation (e.g., van der Laan and Robins, 2003), (ii) using the EIF in a one-step bias correction (e.g., Pfanzagl and Wefelmeyer, 1985), and (iii) using the EIF to construct targeted minimum loss-based estimators (van der Laan and Rubin, 2006; van der Laan and Rose, 2011, 2018).”
Causal mediation analysis for stochastic interventions (2019, methodology): “…approaches for this: (a) using the EIF as an estimating equation (e.g. van der Laan and Robins (2003)), (b) using the EIF in a one-step bias correction (e.g. Pfanzagl and Wefelmeyer (1985)) and (c) targeted minimum loss estimation (van der Laan and Rubin, 2006; van der Laan and Rose, 2011, 2018).”