Deprecated: $wgMWOAuthSharedUserIDs=false is deprecated, set $wgMWOAuthSharedUserIDs=true, $wgMWOAuthSharedUserSource='local' instead [Called from MediaWiki\HookContainer\HookContainer::run in /var/www/html/w/includes/HookContainer/HookContainer.php at line 135] in /var/www/html/w/includes/Debug/MWDebug.php on line 372
Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love - MaRDI portal

Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love

From MaRDI portal
Publication:3021424

DOI10.1198/tast.2010.10052zbMath1217.62095OpenAlexW2133305600WikidataQ57438475 ScholiaQ57438475MaRDI QIDQ3021424

James S. Hodges, Brian J. Reich

Publication date: 25 July 2011

Published in: The American Statistician (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/tast.2010.10052




Related Items (58)

Restricted Spatial Regression Methods: Implications for InferenceStructural Equation Models for Dealing With Spatial ConfoundingJoint temporal point pattern models for proximate species occurrence in a fixed area using camera trap dataBayesian methods for estimating animal abundance at large spatial scales using data from multiple sourcesImproving the usability of spatial point process methodology: an interdisciplinary dialogue between statistics and ecologyA Bayesian Spatial Analysis of the Heterogeneity in Human Mobility Changes During the First Wave of the COVID-19 Epidemic in the United StatesStatistical Implications of Endogeneity Induced by Residential Segregation in Small-Area Modeling of Health InequitiesOn Deconfounding Spatial Confounding in Linear ModelsSpatial Confounding in Generalized Estimating EquationsA spectral method for spatial downscalingSpatial functional data modeling of plant reflectancesThe Bayesian group Lasso for confounded spatial dataSome recent work on multivariate Gaussian Markov random fieldsSpatial regression and spillover effects in cluster randomized trials with count outcomesSpatial+: A novel approach to spatial confoundingDiscussion on “Spatial+: a novel approach to spatial confounding” by Emiko Dupont, Simon N. Wood, and Nicole H. AugustinRejoinder to the discussions of “Spatial+: A novel approach to spatial confounding”A Review of Spatial Causal Inference Methods for Environmental and Epidemiological ApplicationsA flexible Bayesian nonconfounding spatial model for analysis of dispersed count dataA comparison of adaptive sampling designs and binary spatial models : a simulation study using a census of Bromus inermisGeostatistical Methods for Disease Mapping and Visualisation Using Data from Spatio‐temporally Referenced Prevalence SurveysOn the Effects of Spatial Confounding in Hierarchical ModelsComputational aspects of the EM algorithm for spatial econometric models with missing dataEvaluating recent methods to overcome spatial confoundingEvaluation of Bayesian multiple stage estimation under spatial CAR model variantsRecognition and variable selection in sparse spatial panel data models with fixed effectsRestricted spatial regression in practice: geostatistical models, confounding, and robustness under model misspecificationA shared neighbor conditional autoregressive model for small area spatial dataFast, Approximate Maximum Likelihood Estimation of Log-Gaussian Cox ProcessesPopulation counts along elliptical habitat contours: hierarchical modeling using Poisson-lognormal mixtures with nonstationary spatial structureReducing the uncertainty of wildlife population abundance: model‐based versus design‐based estimatesMeasurement error in two‐stage analyses, with application to air pollution epidemiologySpatio‐temporal Bayesian model selection for disease mappingThe importance of scale for spatial-confounding bias and precision of spatial regression estimatorsInducing high spatial correlation with randomly edge-weighted neighborhood graphsAdditive multivariate Gaussian processes for joint species distribution modeling with heterogeneous dataBayesian 2-stage space-time mixture modeling with spatial misalignment of the exposure in small area health dataModeling complex spatial dependencies: low-rank spatially varying cross-covariances with application to soil nutrient dataComputationally efficient multivariate spatio-temporal models for high-dimensional count-valued data (with discussion)A Bayesian localized conditional autoregressive model for estimating the health effects of air pollutionModelling multilevel spatial behaviour in binary-mark muscle fibre configurationsBayesian analysis of spatial generalized linear mixed models with Laplace moving average random fieldsA generalized Gaussian process model for computer experiments with binary time seriesSpatial regression and estimation of disease risks: A clustering‐based approachA hitchhiker's view on spatial statistics and spatial econometrics for lattice dataA Computationally Efficient Projection-Based Approach for Spatial Generalized Linear Mixed ModelsEstimating acute air pollution health effects from cohort study dataAlleviating spatial confounding for areal data problems by displacing the geographical centroidsBayesian zero-inflated negative binomial regression based on Pólya-gamma mixturesSpectral parameterization for linear mixed models applied to confounding of fixed effects by random effectsMitigating unobserved spatial confounding when estimating the effect of supermarket access on cardiovascular disease deathsMSPOCK: alleviating spatial confounding in multivariate disease mapping modelsModeling obesity rate with spatial auto-correlation: a case studyA semivarying joint model for longitudinal binary and continuous outcomesComments on: process modeling for slope and aspect with application to elevation data mapsBayesian binomial mixture models for estimating abundance in ecological monitoring studiesModeling Dependence in Spatio-Temporal EconometricsEstimation and selection for spatial confounding regression models


Uses Software



This page was built for publication: Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love