Cover Image

Kpop: A kernel balancing approach for reducing specification assumptions in survey weighting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hartman, Erin, Hazlett, Chad, Sterbenz, Ciara
Format:	Preprint
Published:	2021
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Sensitivity of weighted least squares estimators to omitted variables
by: Wainstein, Leonard, et al.
Published: (2025)

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

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

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)

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)

A tutorial for propensity score weighting methods under violations of the positivity assumption
by: Liu, Yi, et al.
Published: (2025)

Optimal Survival Analyses With Prevalent and Incident Patients
by: Hartman, Nicholas
Published: (2024)

Accommodating informative visit times for analysing irregular longitudinal data: a sensitivity analysis approach with balancing weights estimators
by: Yiu, Sean, et al.
Published: (2023)

Surrogate-based ABC matches generalized Bayesian inference under specific discrepancy and kernel choices
by: Järvenpää, Marko, et al.
Published: (2025)

A joint longitudinal-survival framework for dynamic treatment regimen evaluation in sequential multiple assignment randomized trials
by: Chen, Zhengxi, et al.
Published: (2026)

Impact of methodological assumptions and covariates on the cutoff estimation in ROC analysis
by: Ghosal, Soutik
Published: (2024)

Recanting witness and natural direct effects: Violations of assumptions or definitions?
by: Shrier, Ian
Published: (2024)

Augmented balancing weights as linear regression
by: Bruns-Smith, David, et al.
Published: (2023)

Quantile balancing inverse probability weighting for non-probability samples
by: Beręsewicz, Maciej, et al.
Published: (2024)

A reduced-rank approach to predicting multiple binary responses through machine learning
by: Mai, The Tien
Published: (2023)

Adaptive weighted approach for high-dimensional statistical learning and inference
by: Lu, Jun, et al.
Published: (2022)

Targeted Parameter Estimation for Robust Empirical Bayes Ranking
by: Henderson, Nicholas C., et al.
Published: (2025)

Dynamic functional brain connectivity results depend on modeling assumptions: comparing frequentist and Bayesian hypothesis tests
by: Huijsdens, Hester, et al.
Published: (2025)

Meta-analysis models relaxing the random effects normality assumption: methodological systematic review and simulation study
by: Panagiotopoulou, Kanella, et al.
Published: (2024)

Finding network effect of randomized treatment under weak assumptions for any outcome and any effect heterogeneity
by: Lee, Myoung-jae
Published: (2025)

A linear mixed model approach for measurement error adjustment: applications to sedentary behavior assessment from wearable devices
by: Chen, Ruohui, et al.
Published: (2024)

Moving toward best practice when using propensity score weighting in survey observational studies
by: Zeng, Yukang, et al.
Published: (2025)

Causal inference under transportability assumptions for conditional relative effect measures
by: Wang, Guanbo, et al.
Published: (2024)

Propensity weighting plus adjustment in proportional hazards model is not doubly robust
by: Gabriel, Erin E, et al.
Published: (2023)

A dimension reduction approach to edge weight estimation for use in spatial models
by: Christensen, Michael F., et al.
Published: (2024)

Dimension-reduced outcome-weighted learning for estimating individualized treatment regimes in observational studies
by: Son, Sungtaek, et al.
Published: (2026)

A Null Model for Mapper Subtype Claims
by: Topaz, Chad M.
Published: (2026)

Doubly robust causal inference through penalized bias-reduced estimation: combining non-probability samples with designed surveys
by: Du, Jiacong, et al.
Published: (2024)

Generalized projection tests for function-valued parameters with applications to testing structural causal assumptions
by: Wang, Rui, et al.
Published: (2026)

A path-specific effect approach to mediation analysis with time-varying mediators and time-to-event outcomes accounting for competing risks
by: Domingo-Relloso, Arce, et al.
Published: (2024)

Identification of complier and noncomplier average causal effects in the presence of latent missing-at-random (LMAR) outcomes: a unifying view and choices of assumptions
by: Nguyen, Trang Quynh, et al.
Published: (2023)

Gaussian Process with dissolution spline kernel
by: Murphy, Fiona, et al.
Published: (2024)

Shrinkage MMSE estimators of covariances beyond the zero-mean and stationary variance assumptions
by: Flasseur, Olivier, et al.
Published: (2024)

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

On the interplay between prior weight and variance of the robustification component in Robust Mixture Prior Bayesian Dynamic Borrowing approach
by: Ratta, Marco, et al.
Published: (2025)

Publication bias adjustment in network meta-analysis: an inverse probability weighting approach using clinical trial registries
by: Huang, Ao, et al.
Published: (2024)

Wrapped flat-top kernel density estimation with circular data
by: Tsuruta, Yasuhito
Published: (2026)

Mahalanobis balancing: a multivariate perspective on approximate covariate balancing
by: Dai, Yimin, et al.
Published: (2022)

Covariate balancing estimation and model selection for difference-in-differences approach
by: Baba, Takamichi, et al.
Published: (2025)