Results 11 to 20 of about 15,773 (265)

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

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   +3 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

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

Which misspecifications persist?

open access: yesTheoretical Economics, 2023
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
openaire   +2 more sources

Confronting model misspecification in macroeconomics [PDF]

open access: yesJournal of Econometrics, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Daniel F. Waggoner, Tao Zha
openaire   +4 more sources

Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification

open access: yesEconometrics, 2015
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
doaj   +1 more source

An Information Criterion for Auxiliary Variable Selection in Incomplete Data Analysis

open access: yesEntropy, 2019
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
doaj   +1 more source

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

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