The International Journal of Biostatistics
Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.
2 Issues per year
IMPACT FACTOR 2016: 0.500
5-year IMPACT FACTOR: 0.862
CiteScore 2016: 0.42
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Source Normalized Impact per Paper (SNIP) 2016: 0.467
Mathematical Citation Quotient (MCQ) 2016: 0.09
Consider the simple setting of point exposure, outcome and confounding variables, all of which are discrete. As is well known, parametric modeling of outcome given exposure and confounders and also exposure given confounders can yield a double-robust estimator. This has the property of being consistent as long as at least one of the two specified models is correct. Such an estimator can also be cast as arising from a compromise between the parametric outcome model and a nonparametric or saturated outcome model. This brings to mind an alternate compromise based on Bayesian model averaging, and prompts comparisons between the double-robust method and the Bayesian method.
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