Results 11 to 20 of about 16,351 (263)

Selection Consistency of Lasso-Based Procedures for Misspecified High-Dimensional Binary Model and Random Regressors

open access: yesEntropy, 2020
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
doaj   +1 more source

Model Misspecification as the Causes of Flypaper Effect

open access: yesProceedings, 2023
The aim of this paper is to investigate the relationship between the Fly-paper effect (FPE) and possible errors in the specification of econometric models used in the empirical analysis of FPE.
Siniša Mali
doaj   +1 more source

Evaluating performance of covariate-constrained randomization (CCR) techniques under misspecification of cluster-level variables in cluster-randomized trials

open access: yesContemporary Clinical Trials Communications, 2021
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
doaj   +1 more source

Model misspecification [PDF]

open access: yesStatistical Modelling, 2008
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
openaire   +4 more sources

MTE with Misspecification

open access: yes, 2022
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
openaire   +2 more sources

Minimizing sensitivity to model misspecification [PDF]

open access: yesQuantitative Economics, 2022
We propose a framework for estimation and inference when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We construct estimators whose mean squared error is minimax in a neighborhood of the reference model, based on one‐step adjustments.
Weidner, Martin, Bonhomme, Stéphane
openaire   +7 more sources

A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function

open access: yesPopulation Health Metrics, 2012
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
doaj   +1 more source

Adapting to Misspecification in Contextual Bandits

open access: yesCoRR, 2021
Appeared at NeurIPS ...
Dylan J. Foster   +3 more
openaire   +3 more sources

An improved multiply robust estimator for the average treatment effect

open access: yesBMC Medical Research Methodology, 2023
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
doaj   +1 more source

Robust control and model misspecification [PDF]

open access: yesJournal of Economic Theory, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lars Peter Hansen   +3 more
openaire   +1 more source

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