Cover Image

Sensitivity of weighted least squares estimators to omitted variables

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wainstein, Leonard, Hazlett, Chad
Format:	Preprint
Published:	2025
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Demystifying and avoiding the OLS "weighting problem": Unmodeled heterogeneity and straightforward solutions
by: Shinkre, Tanvi, et al.
Published: (2024)

Subscedastic weighted least squares estimates
by: Bryan, Jordan, et al.
Published: (2024)

Kpop: A kernel balancing approach for reducing specification assumptions in survey weighting
by: Hartman, Erin, et al.
Published: (2021)

Inference with weights: Residualization produces short, valid intervals for varying estimands and varying resampling processes
by: Hartman, Erin, et al.
Published: (2025)

Causal progress with imperfect placebo treatments and outcomes
by: Rohde, Adam, et al.
Published: (2023)

Weighted least squares estimation by multivariate-dependent weights for linear regression models
by: Huang, Lei, et al.
Published: (2026)

Targeted Function Balancing
by: Wainstein, Leonard, et al.
Published: (2022)

Profile least squares estimation in networks with covariates
by: Chandna, Swati, et al.
Published: (2024)

Recent advances in doubly-robust weighted ordinary least squares techniques for dynamic treatment regime estimation
by: Nadi, Adel Ahmadi, et al.
Published: (2025)

Post-treatment problems: What can we say about the effect of a treatment among sub-groups who (would) respond in some way?
by: Hazlett, Chad, et al.
Published: (2025)

Two-stage weighted least squares estimator of multivariate non-negative observation-driven models
by: Armillotta, Mirko
Published: (2023)

Ridge-penalised spectral least-squares estimation for point processes
by: Herrera, Miguel Martinez, et al.
Published: (2026)

Multivariate moment least-squares estimators for reversible Markov chains
by: Song, Hyebin, et al.
Published: (2023)

Inference at the data's edge: Gaussian processes for modeling and inference under model-dependency, poor overlap, and extrapolation
by: Cho, Soonhong, et al.
Published: (2024)

Phylogenetic least squares estimation without genetic distances
by: Chi, Peter B., et al.
Published: (2023)

A penalized least squares estimator for extreme-value mixture models
by: Mourahib, Anas, et al.
Published: (2025)

Comparing multilevel and fixed effect approaches in the generalized linear model setting
by: Bai, He, et al.
Published: (2024)

Constrained least squares simplicial-simplicial regression
by: Tsagris, Michail
Published: (2024)

Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in estimating the mean squared error of the least squares estimator in linear regression
by: Stolte, Marieke, et al.
Published: (2023)

Directional replicability: when can the factor of two be omitted
by: Djordjilović, Vera, et al.
Published: (2025)

Envelope-based partial least squares in functional regression
by: Wu, Minxuan, et al.
Published: (2025)

Generalised least squares approach for estimation of the log-law parameters of turbulent boundary layers
by: Ferreira, M. Aguiar, et al.
Published: (2026)

Sparse higher order partial least squares for simultaneous variable selection, dimension reduction, and tensor denoising
by: Park, Kwangmoon, et al.
Published: (2023)

Ridge, lasso, and elastic-net estimations of the modified Poisson and least-squares regressions for binary outcome data
by: Kitano, Takahiro, et al.
Published: (2024)

Two-stage least squares with treatment-covariate interactions for treatment effect heterogeneity
by: Zhao, Anqi, et al.
Published: (2025)

A constrained iteratively-reweighted least-squares framework for generalised linear models
by: Masselot, Pierre, et al.
Published: (2025)

Structured Lasso for convex nonparametric least squares: An application to Swedish electricity distribution networks
by: Liao, Zhiqiang, et al.
Published: (2024)

With random regressors, least squares inference is robust to correlated errors with unknown correlation structure
by: Zhang, Zifeng, et al.
Published: (2024)

Fast algorithm for sparse least trimmed squares via trimmed-regularized reformulation
by: Yagishita, Shotaro
Published: (2024)

Predicting milk traits from spectral data using Bayesian probabilistic partial least squares regression
by: Urbas, Szymon, et al.
Published: (2023)

Scalable approximation of the transformation-free linear simplicial-simplicial regression via constrained iterative reweighted least squares
by: Tsagris, Michail, et al.
Published: (2025)

Identifiability and improper solutions in the probabilistic partial least squares regression with unique variance
by: Arai, Takashi
Published: (2025)

A joint optimization approach to identifying sparse dynamics using least squares kernel collocation
by: Hsu, Alexander W., et al.
Published: (2025)

A least distance estimator for a multivariate regression model using deep neural networks
by: Shin, Jungmin, et al.
Published: (2024)

Augmented match weighted estimators for average treatment effects
by: Xu, Tanchumin, et al.
Published: (2023)

Unbiased least squares regression via averaged stochastic gradient descent
by: Kahalé, Nabil
Published: (2024)

Adjusted Nelson--Aalen estimators by inverse treatment probability weighting with an estimated propensity score
by: Deng, Yuhao, et al.
Published: (2024)

On the use of the principle of maximum entropy to improve the robustness of bivariate spline least-squares approximation
by: Amodio, Pierluigi, et al.
Published: (2025)

The Generalized Elastic Net for least squares regression with network-aligned signal and correlated design
by: Tran, Huy, et al.
Published: (2022)

Improving instrumental variable estimators with post-stratification
by: Pashley, Nicole E., et al.
Published: (2023)