kpop: a kernel balancing approach for reducing specification assumptions in survey weighting [0.03%]
基于KPOP内核平衡的调查加权方法：减少规范假设的影响
Erin Hartman,Chad Hazlett,Ciara Sterbenz
Erin Hartman
With the precipitous decline in response rates, researchers and pollsters have been left with highly nonrepresentative samples, relying on constructed weights to make these samples representative of the desired target population. Though pra...
Graphical displays and related statistical measures of health disparities between groups in complex sample surveys [0.03%]
复杂抽样调查中图形显示及相关的统计指标在群体健康差异性分析中的应用
Mark Louie Ramos,Barry Graubard,Joseph Gastwirth
Mark Louie Ramos
Different methods for describing health disparities in the distributions of continuous measured health-related variables among groups provide more insight into the nature and impact of the disparities than comparing measures of central tend...
Doubly robust machine learning-based estimation methods for instrumental variables with an application to surgical care for cholecystitis [0.03%]
基于仪器变量的双重稳健机器学习估计方法及其在胆囊炎手术治疗中的应用
Kenta Takatsu,Alexander W Levis,Edward Kennedy et al.
Kenta Takatsu et al.
Comparative effectiveness research frequently employs the instrumental variable design since randomized trials can be infeasible for many reasons. In this study, we investigate treatments for emergency cholecystitis-inflammation of the gall...
Optimal risk-assessment scheduling for primary prevention of cardiovascular disease [0.03%]
心血管病一级预防的理想风险评估及干预时机
Francesca Gasperoni,Christopher H Jackson,Angela M Wood et al.
Francesca Gasperoni et al.
In this work, we introduce a personalized and age-specific net benefit function, composed of benefits and costs, to recommend optimal timing of risk assessments for cardiovascular disease (CVD) prevention. We extend the 2-stage landmarking ...
A Bayesian spatial-temporal varying coefficients model for estimating excess deaths associated with respiratory infections [0.03%]
一种用于估计与呼吸道感染相关的超额死亡的贝叶斯时空可变系数模型
Yuzi Zhang,Howard H Chang,Angela D Iuliano et al.
Yuzi Zhang et al.
Disease surveillance data are used for monitoring and understanding disease burden, which provides valuable information in allocating health programme resources. Statistical methods play an important role in estimating disease burden since ...
Mapping socio-economic status using mixed data: a hierarchical Bayesian approach [0.03%]
使用混合数据进行社会经济地位的制图研究：一种分层贝叶斯方法
Gabrielle Virgili-Gervais,Alexandra M Schmidt,Honor Bixby et al.
Gabrielle Virgili-Gervais et al.
We propose a Bayesian hierarchical model to estimate a socio-economic status (SES) index based on mixed dichotomous and continuous variables. In particular, we extend Quinn's ([2004]. Bayesian factor analysis for mixed ordinal and continuou...
Data-integration with pseudoweights and survey-calibration: application to developing US-representative lung cancer risk models for use in screening [0.03%]
基于伪权重的数据整合与调查校准：在美国肺癌筛查中建立具有代表性的肺癌风险模型的应用
Lingxiao Wang,Yan Li,Barry I Graubard et al.
Lingxiao Wang et al.
Accurate cancer risk estimation is crucial to clinical decision-making, such as identifying high-risk people for screening. However, most existing cancer risk models incorporate data from epidemiologic studies, which usually cannot represen...
A comparison of some existing and novel methods for integrating historical models to improve estimation of coefficients in logistic regression [0.03%]
几种用于历史模型融合以改善逻辑回归系数估计的现有方法和新型方法的比较
Philip S Boonstra,Pedro Orozco Del Pino
Philip S Boonstra
Model integration refers to the process of incorporating a fitted historical model into the estimation of a current study to increase statistical efficiency. Integration can be challenging when the current model includes new covariates, lea...
Studying Chinese immigrants' spatial distribution in the Raleigh-Durham area by linking survey and commercial data using romanized names [0.03%]
利用罗曼化名称链接调查数据和商业数据研究夏洛特地区华人分布特征
Eric A Bai,Botao Ju,Madeleine Beckner et al.
Eric A Bai et al.
Many population surveys do not provide information on respondents' residential addresses, instead offering coarse geographies like zip code or higher aggregations. However, fine resolution geography can be beneficial for characterizing neig...