Results 21 to 30 of about 29,799 (296)
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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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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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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Adapting to Misspecification in Contextual Bandits
Appeared at NeurIPS ...
Dylan J. Foster +3 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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Consequences of Model Misspecification for Maximum Likelihood Estimation with Missing Data
Researchers are often faced with the challenge of developing statistical models with incomplete data. Exacerbating this situation is the possibility that either the researcher’s complete-data model or the model of the missing-data mechanism is ...
Richard M. Golden +3 more
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Robust control and model misspecification [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lars Peter Hansen +3 more
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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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Likelihood-based estimation and prediction for a measles outbreak in Samoa
Prediction of the progression of an infectious disease outbreak is important for planning and coordinating a response. Differential equations are often used to model an epidemic outbreak's behaviour but are challenging to parameterise. Furthermore, these
David Wu +4 more
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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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