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7 papers · 1 filter
Nonparametric causal mediation analysis for stochastic interventional (in)direct effects
Nima S. Hejazi, Kara E. Rudolph, Mark J. van der Laan +1
Causal mediation analysis has historically been limited in two important ways: (i) a focus has traditionally been placed on binary treatments and static interventions, and (ii) dir…
Multiblock variable influence on orthogonal projections (MB-VIOP) for enhanced interpretation of total, global, local and unique variations in OnPLS models
B. Galindo-Prieto, P. Geladi, J. Trygg
For multivariate data analysis involving only two input matrices, the previously published methods for variable influence on projection (e.g., VIPOPLS or VIPO2PLS) are widely used…
Non-parametric efficient causal mediation with intermediate confounders
Iván Díaz, Nima S. Hejazi, Kara E. Rudolph +1
Interventional effects for mediation analysis were proposed as a solution to the lack of identifiability of natural (in)direct effects in the presence of a mediator-outcome confoun…
Causal mediation analysis for stochastic interventions
Iván Díaz, Nima Hejazi
Mediation analysis in causal inference has traditionally focused on binary exposures and deterministic interventions, and a decomposition of the average treatment effect in terms o…
On the number of principal components in high dimensions
Sungkyu Jung, Myung Hee Lee, Jeongyoun Ahn
We consider the problem of how many components to retain in the application of principal component analysis when the dimension is much higher than the number of observations. To es…
Doubly Robust Inference for Targeted Minimum Loss Based Estimation in Randomized Trials with Missing Outcome Data
Iván Díaz, Mark J. van der Laan
Missing outcome data is one of the principal threats to the validity of treatment effect estimates from randomized trials. The outcome distributions of participants with missing an…