Develops stochastic policies and single-basis-function modification for causal inference on functional treatments, proves asymptotic normality and rate double robustness, and applies to NHANES physical activity and mortality data.
and Caffo, Brian and Reich, Daniel , number =
2 Pith papers cite this work, alongside 283 external citations. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
A new MFPCA approach for variable domain data is proposed by running univariate variable-domain FPCA on each variable, stacking the scores, and smoothing the empirical covariance matrix over domain length to recover joint eigenfunctions and scores.
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Causal Inference for Functional Treatments with Stochastic Policies
Develops stochastic policies and single-basis-function modification for causal inference on functional treatments, proves asymptotic normality and rate double robustness, and applies to NHANES physical activity and mortality data.
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Variable Domain Multivariate Functional Principal Component Analysis
A new MFPCA approach for variable domain data is proposed by running univariate variable-domain FPCA on each variable, stacking the scores, and smoothing the empirical covariance matrix over domain length to recover joint eigenfunctions and scores.