In this article,a new unit level model based on a pairwise penalised regression approach is proposed for problems in small area estimation(SAE).Instead of assuming common regression coefficients for all small domains ...In this article,a new unit level model based on a pairwise penalised regression approach is proposed for problems in small area estimation(SAE).Instead of assuming common regression coefficients for all small domains in the traditional model,the new estimator is based on a subgroup regression model which allows different regression coefficients in different groups.The alternating direction method of multipliers(ADMM)algorithm is used to find subgroups with different regression coefficients.We also consider pairwise spatial weights for spatial areal data.In the simulation study,we compare the performances of the new estimator with the traditional small area estimator.We also apply the new estimator to urban area estimation using data from the National Resources Inventory survey in Iowa.展开更多
Meta-analysis is an important statistical tool,and it is often used to solve clinical problems.However inevitably when conducting a meta-analysis,the included studies often have heterogeneity.This paper suggests the i...Meta-analysis is an important statistical tool,and it is often used to solve clinical problems.However inevitably when conducting a meta-analysis,the included studies often have heterogeneity.This paper suggests the inclusion of relevant background data or contextual variables into the model.The contextual variables are those variables not explicitly measured in the studies included in a metaanalysis;thus,these must be very well-described and justified as parameters for analyses.展开更多
基金This research was supported in part by the Natural ResourcesConservation Service of the U.S. Department of Agriculture.
文摘In this article,a new unit level model based on a pairwise penalised regression approach is proposed for problems in small area estimation(SAE).Instead of assuming common regression coefficients for all small domains in the traditional model,the new estimator is based on a subgroup regression model which allows different regression coefficients in different groups.The alternating direction method of multipliers(ADMM)algorithm is used to find subgroups with different regression coefficients.We also consider pairwise spatial weights for spatial areal data.In the simulation study,we compare the performances of the new estimator with the traditional small area estimator.We also apply the new estimator to urban area estimation using data from the National Resources Inventory survey in Iowa.
文摘Meta-analysis is an important statistical tool,and it is often used to solve clinical problems.However inevitably when conducting a meta-analysis,the included studies often have heterogeneity.This paper suggests the inclusion of relevant background data or contextual variables into the model.The contextual variables are those variables not explicitly measured in the studies included in a metaanalysis;thus,these must be very well-described and justified as parameters for analyses.
