Robust best linear weighted estimator with missing covariates in survival analysis
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DOI: 10.1002/sim.10044
Abstract: Missing data in covariates can result in biased estimates and loss of power to detect associations. We consider Cox regression in which some covariates are subject to missing. The inverse probability weighted approach is often… read more here.
Keywords: missing covariates; robust best; weighted estimator; best linear ... See more keywords
Asymptotics for the conditional self-weighted M-estimator of GRCA(1) models with possibly heavy-tailed errors
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DOI: 10.1007/s00362-019-01141-8
Abstract: Consider a generalized random coefficient AR(1) model, $$y_t=\Phi _t y_{t-1}+u_t$$ , where $$\{(\Phi _t, u_t)^\prime , t\ge 1\}$$ is a sequences of i.i.d. random vectors, and a conditional self-weighted M-estimator of $$\textsf {E}\Phi _t$$ is… read more here.
Keywords: estimator; self weighted; weighted estimator; asymptotics conditional ... See more keywords
Optimal Probability Weights for Inference With Constrained Precision
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DOI: 10.1080/01621459.2017.1375932
Abstract: ABSTRACT Probability weights are used in many areas of research including complex survey designs, missing data analysis, and adjustment for confounding factors. They are useful analytic tools but can lead to statistical inefficiencies when they… read more here.
Keywords: probability weights; weighted estimator; precision; weights inference ... See more keywords