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Targeted maximum likelihood estimation (TMLE) is a general approach for constructing an efficient double-robust semi-parametric substitution estimator of a causal effect parameter or statistical association measure. tmle is a recently developed R package that implements TMLE of the effect of a binary treatment at a single point in time on an outcome of interest, controlling for user supplied covariates, including an additive treatment effect, relative risk, odds ratio, and the controlled direct effect of a binary treatment controlling for a binary intermediate variable on the pathway from treatment to the out- come. Estimation of the parameters of a marginal structural model is also available. The package allows outcome data with missingness, and experimental units that contribute repeated records of the point-treatment data structure, thereby allowing the analysis of longitudinal data structures. Relevant factors of the likelihood may be modeled or fit data-adaptively according to user specifications, or passed in from an external estimation procedure. Effect estimates, variances, p values, and 95% confidence intervals are provided by the software.
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Gruber et al. (Sun,) studied this question.
synapsesocial.com/papers/69ffbca3ef8139f8ff776ee7 — DOI: https://doi.org/10.18637/jss.v051.i13
Susan Gruber
Revolution Research
Mark J. van der Laan
University of California, Berkeley
Journal of Statistical Software
University of California, Berkeley
Harvard University Press
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