Kris V Parag,Robin N Thompson,Christl A Donnelly
Kris V Parag
statistics, often derived from simplified models of epidemic spread, inform public health policy in real time. The instantaneous reproduction number, R t , is predominant among these statistics, measuring the average ability of an infect...
Estimating monthly labour force figures during the COVID-19 pandemic in the Netherlands [0.03%]
荷兰在COVID-19疫情期间的月度劳动力数据估算
Jan van den Brakel,Martijn Souren,Sabine Krieg
Jan van den Brakel
Official monthly statistics about the Dutch labour force are based on the Dutch Labour Force Survey (LFS). The LFS is a continuously conducted survey that is designed as a rotating panel design. Data collection among selected households is ...
Comparing the Real-World Performance of Exponential-family Random Graph Models and Latent Order Logistic Models for Social Network Analysis [0.03%]
指数族随机图模型和潜在序 logistic 模型在社会网络分析中的实证比较研究
Duncan A Clark,Mark S Handcock
Duncan A Clark
Exponential-family Random Graph models (ERGM) are widely used in social network analysis when modelling data on the relations between actors. ERGMs are typically interpreted as a snapshot of a network at a given point in time or in a final ...
Removing the influence of group variables in high-dimensional predictive modelling [0.03%]
高维预测模型中剔除群体变量的影响
Emanuele Aliverti,Kristian Lum,James E Johndrow et al.
Emanuele Aliverti et al.
In many application areas, predictive models are used to support or make important decisions. There is increasing awareness that these models may contain spurious or otherwise undesirable correlations. Such correlations may arise from a var...
A simple framework to identify optimal cost-effective risk thresholds for a single screen: Comparison to Decision Curve Analysis [0.03%]
一种识别单次筛查最佳成本效益风险阈值的简单框架：与决策曲线分析比较
Hormuzd A Katki,Ionut Bebu
Hormuzd A Katki
Decision Curve Analysis (DCA) is a popular approach for assessing biomarkers and risk models, but does not require costs and thus cannot identify optimal risk thresholds for actions. Full decision analyses can identify optimal thresholds, b...
Behzod B Ahundjanov,Sherzod B Akhundjanov,Botir B Okhunjanov
Behzod B Ahundjanov
The novel coronavirus (COVID-19) was first identified in China in December 2019. Within a short period of time, the infectious disease has spread far and wide. This study focuses on the distribution of COVID-19 confirmed cases in China-the ...
A multidimensional pairwise comparison model for heterogeneous perceptions with an application to modelling the perceived truthfulness of public statements on COVID-19 [0.03%]
一种异质性感知的多维成对比较模型及其在建模公众关于新冠状病毒肺炎声明真实性的感知上的应用
Qiushi Yu,Kevin M Quinn
Qiushi Yu
Pairwise comparison models are an important type of latent attribute measurement model with broad applications in the social and behavioural sciences. Current pairwise comparison models are typically unidimensional. The existing multidimens...
COVID-19 severity: A new approach to quantifying global cases and deaths [0.03%]
COVID-19的严重性：量化全球病例和死亡的新方法
Daniel L Millimet,Christopher F Parmeter
Daniel L Millimet
As the COVID-19 pandemic has progressed, so too has the recognition that cases and deaths have been underreported, perhaps vastly so. Here, we present an econometric strategy to estimate the true number of COVID-19 cases and deaths for 61 a...
Two-Phase Sampling Designs for Data Validation in Settings with Covariate Measurement Error and Continuous Outcome [0.03%]
具有协变量测量误差和连续结果的两阶段抽样设计以进行数据验证
Gustavo Amorim,Ran Tao,Sarah Lotspeich et al.
Gustavo Amorim et al.
Measurement errors are present in many data collection procedures and can harm analyses by biasing estimates. To correct for measurement error, researchers often validate a subsample of records and then incorporate the information learned f...
A Bayesian multivariate factor analysis model for evaluating an intervention by using observational time series data on multiple outcomes [0.03%]
一种贝叶斯多元因素分析模型：利用观察时间序列数据对多种结果的干预措施进行评价
Pantelis Samartsidis,Shaun R Seaman,Silvia Montagna et al.
Pantelis Samartsidis et al.
A problem that is frequently encountered in many areas of scientific research is that of estimating the effect of a non-randomized binary intervention on an outcome of interest by using time series data on units that received the interventi...