DeepAI AI Chat
Log In Sign Up

Targeting Learning: Robust Statistics for Reproducible Research

06/12/2020
by   Jeremy R. Coyle, et al.
3

Targeted Learning is a subfield of statistics that unifies advances in causal inference, machine learning and statistical theory to help answer scientifically impactful questions with statistical confidence. Targeted Learning is driven by complex problems in data science and has been implemented in a diversity of real-world scenarios: observational studies with missing treatments and outcomes, personalized interventions, longitudinal settings with time-varying treatment regimes, survival analysis, adaptive randomized trials, mediation analysis, and networks of connected subjects. In contrast to the (mis)application of restrictive modeling strategies that dominate the current practice of statistics, Targeted Learning establishes a principled standard for statistical estimation and inference (i.e., confidence intervals and p-values). This multiply robust approach is accompanied by a guiding roadmap and a burgeoning software ecosystem, both of which provide guidance on the construction of estimators optimized to best answer the motivating question. The roadmap of Targeted Learning emphasizes tailoring statistical procedures so as to minimize their assumptions, carefully grounding them only in the scientific knowledge available. The end result is a framework that honestly reflects the uncertainty in both the background knowledge and the available data in order to draw reliable conclusions from statistical analyses - ultimately enhancing the reproducibility and rigor of scientific findings.

READ FULL TEXT

page 20

page 24

page 26

07/25/2022

Semiparametric Estimation on Multi-treatment Causal Effects via Cross-Fitting

Causal inference is a critical research area with multi-disciplinary ori...
04/11/2023

Targeted Maximum Likelihood Based Estimation for Longitudinal Mediation Analysis

Causal mediation analysis with random interventions has become an area o...
09/07/2018

A Primer on Causality in Data Science

Many questions in Data Science are fundamentally causal in that our obje...
05/27/2017

Targeted Learning with Daily EHR Data

Electronic health records (EHR) data provide a cost and time-effective o...
10/07/2022

Efficient and Robust Approaches for Analysis of SMARTs: Illustration using the ADAPT-R Trial

Personalized intervention strategies, in particular those that modify tr...
05/17/2022

Targeted learning: Towards a future informed by real-world evidence

The 21st Century Cures Act of 2016 includes a provision for the U.S. Foo...
04/03/2023

Connecting Simple and Precise P-values to Complex and Ambiguous Realities

Mathematics is a limited component of solutions to real-world problems, ...