Developing a Targeted Learning-Based Statistical Analysis Plan

Presented by Susan Gruber. When the goal is to estimate causal effects from data it is crucial to pre-specify the entire data analysis. This is especially important when using data-adaptive statistical methodology, in order to ensure interpretable results are obtained from a valid, reproducible analyses. We’ll consider a sample Targeted Learning (TL)-based statistical analysis plan that illustrates how the TL Roadmap can guide handling of intercurrent events, as described in ICH E9 (R1) Guidelines. We also introduce checklists for fully documenting the analytic specifications of an analysis using TMLE and super learning.

[mvai]

Thanks for making this talk public - a great resource. Interested in whether you might be able to provide a reference for the sensitivity method presented around 37:50. Is this similar to the approach presented in Diaz and van der Laan (2013)?