Results 1 to 10 of about 61 (29)
Causal effect on a target population: A sensitivity analysis to handle missing covariates
Journal of Causal Inference, 2022 Randomized controlled trials (RCTs) are often considered the gold standard for estimating causal effect, but they may lack external validity when the population eligible to the RCT is substantially different from the target population.
Colnet Bénédicte +3 more
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A fundamental measure of treatment effect heterogeneity
Journal of Causal Inference, 2021 The stratum-specific treatment effect function is a random variable giving the average treatment effect (ATE) for a randomly drawn stratum of potential confounders a clinician may use to assign treatment.
Levy Jonathan +3 more
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Journal of Causal Inference, 2022 Analysts often use data-driven approaches to supplement their knowledge when selecting covariates for effect estimation. Multiple variable selection procedures for causal effect estimation have been devised in recent years, but additional developments ...
Talbot Denis, Beaudoin Claudia
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Journal of Causal Inference, 2022 Recent studies have indicated that it is possible to protect individuals from HIV infection using passive infusion of monoclonal antibodies. However, in order for monoclonal antibodies to confer robust protection, the antibodies must be capable of ...
Jin Yutong, Benkeser David
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Open Mathematics, 2022 In this article, we present a new robust estimation procedure based on the exponential squared loss function for varying coefficient partially functional linear regression models, where the slope function and nonparametric coefficients are approximated ...
Sun Jun, Liu Wanrong
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Two symmetric and computationally efficient Gini correlations
Dependence Modeling, 2020 Standard Gini correlation plays an important role in measuring the dependence between random variables with heavy-tailed distributions. It is based on the covariance between one variable and the rank of the other. Hence for each pair of random variables,
Vanderford Courtney +2 more
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Asymptotic properties of predictive recursion: Robustness and rate of convergence
, 2009 Here we explore general asymptotic properties of Predictive Recursion (PR) for nonparametric estimation of mixing distributions. We prove that, when the mixture model is mis-specified, the estimated mixture convergesalmost surely in total variation to ...
Ryan Martin, S. Tokdar
semanticscholar +1 more source
Affine-invariant rank tests for multivariate independence in independent component models
, 2016 We consider the problem of testing for multivariate indepen- dence in independent component (IC) models. Under a symmetry assump- tion, we develop parametric and nonparametric (signed-rank) tests.
H. Oja, D. Paindaveine, S. Taskinen
semanticscholar +1 more source
, 2016 Understanding efficiency in high dimensional linear models is a longstanding problem of interest. Classical work with smaller dimensional problems dating back to Huber and Bickel has illustrated the clear benefits of efficient loss functions.
Jelena Bradic
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Multinomial goodness-of-fit tests under inlier modification
, 2011 The Pearson’s chi-square and the log-likelihood ratio chi-square statistics are fundamental tools in multinomial goodness-of-fit testing. Cressie and Read (1984) constructed a general family of divergences which includes both statistics as special cases.
A. Mandal, A. Basu
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