專題演講 主講人:陳春樹教授(中央大學統計研究所)

  • 2021-04-30
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題 目:An advanced approach to unmeasured spatial confounders

主講人:陳春樹教授(中央大學統計所)

時 間:110年4月30日(星期五)上午10:40-11:30

(上午10:20-10:40茶會於交大統計所428室舉行) 

地 點:交大綜合一館427室
 
摘要
 
In spatial regression analysis, collinearity between covariates and spatial random effects can lead to significant bias in the fixed effect estimate. This issue is known as spatial confounding. A reliable inference is difficult due to unobserved spatial random effects. Some techniques under restricted spatial regression had been proposed to investigate this issue, but how to modify the bias of regression coefficient estimators remains an active research topic. We propose an adjusted generalized least squares estimation method to estimate regression coefficients in the presence of spatial confounding and its superiorities are demonstrated by theories and simulations. Some concerns about the proposed approach are also discussed. Finally, a real data example is analyzed for illustration.
 


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