Results 11 to 20 of about 15,773 (265)
We consider selection of random predictors for a high-dimensional regression problem with a binary response for a general loss function. An important special case is when the binary model is semi-parametric and the response function is misspecified under
Mariusz Kubkowski, Jan Mielniczuk
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Covariate constrained randomization (CCR) is a method of controlling imbalance in important baseline covariates in cluster-randomized trials (CRT). We use simulated CRTs to investigate the performance (control of imbalance) of CCR relative to simple ...
Madeleine Organ +5 more
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A common problem in statistical modelling is to distinguish between finite mixture distribution and a homogeneous non-mixture distribution. Finite mixture models are widely used in practice and often mixtures of normal densities are indistinguishable from homogenous non-normal densities.
Tarpey, Thaddeus +2 more
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A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function
Background The EQ-5D is a generic health-related quality of life instrument (five dimensions with three levels, 243 health states), used extensively in cost-utility/cost-effectiveness analyses.
Rand-Hendriksen Kim +2 more
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An improved multiply robust estimator for the average treatment effect
Background In observational studies, double robust or multiply robust (MR) approaches provide more protection from model misspecification than the inverse probability weighting and g-computation for estimating the average treatment effect (ATE). However,
Ce Wang +4 more
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Which misspecifications persist?
We use an evolutionary model to determine which misperceptions can persist. Every period, a new generation of agents use their subjective models and the data generated by the previous generation to update their beliefs, and models that induce better actions become more prevalent.
Fudenberg, Drew, Lanzani, Giacomo
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Confronting model misspecification in macroeconomics [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Daniel F. Waggoner, Tao Zha
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Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification
Allowing for misspecification in the linear conditional quantile function, this paper provides a new interpretation and the semiparametric efficiency bound for the quantile regression parameter β (
Ying-Ying Lee
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An Information Criterion for Auxiliary Variable Selection in Incomplete Data Analysis
Statistical inference is considered for variables of interest, called primary variables, when auxiliary variables are observed along with the primary variables.
Shinpei Imori, Hidetoshi Shimodaira
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This paper studies the implication of a fraction of the population not responding to the instrument when selecting into treatment. We show that, in general, the presence of non-responders biases the Marginal Treatment Effect (MTE) curve and many of its functionals. Yet, we show that, when the propensity score is fully supported on the unit interval, it
Martínez-Iriarte, Julián +1 more
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