Test Statistics and Statistical Inference for Data With Informative Cluster Sizes [0.03%]
具有丰富集群规模的数据的检验统计量和统计推断
Soyoung Kim,Michael J Martens,Kwang Woo Ahn
Soyoung Kim
In biomedical studies, investigators often encounter clustered data. The cluster sizes are said to be informative if the outcome depends on the cluster size. Ignoring informative cluster sizes in the analysis leads to biased parameter estim...
Detecting Interactions in High-Dimensional Data Using Cross Leverage Scores [0.03%]
基于交叉杠杆性的高维数据分析交互作用的方法
Sven Teschke,Katja Ickstadt,Alexander Munteanu
Sven Teschke
We develop a variable selection method for interactions in regression models on large data in the context of genetics. The method is intended for investigating the influence of single-nucleotide polymorphisms (SNPs) and their interactions o...
A Matched Design for Causal Inference With Survey Data: Evaluation of Medical Marijuana Legalization in Kentucky and Tennessee [0.03%]
基于调查数据的因果推理匹配设计：肯塔基州和田纳西州医用大麻合法化的评估
Marco H Benedetti,Bo Lu,Motao Zhu
Marco H Benedetti
A concern surrounding marijuana legalization is that driving after marijuana use may become more prevalent. Survey data are valuable for estimating policy effects, however their observational nature and unequal sampling probabilities create...
[Formula: see text] -Inflated Beta Regression Model for Estimating [Formula: see text] -Restricted Means and Event-Free Probabilities for Censored Time-to-Event Data [0.03%]
用于估计截断均值和删失时间结果的无事件概率的[公式：请参见文本]-膨胀Beta回归模型
Yizhuo Wang,Susan Murray
Yizhuo Wang
In this research, we propose analysis of τ $/tau$ -restricted censored time-to-event data via a τ $/tau$ -inflated beta regression ( τ $/tau$ -IBR) model. The outcome of interest is min ( τ , T ) ${/rm min}(/tau,T)$ ...
Risk-Based Decision Making: Estimands for Sequential Prediction Under Interventions [0.03%]
基于风险的决策制定：干预下的序列预测估量对象
Kim Luijken,Paweł Morzywołek,Wouter van Amsterdam et al.
Kim Luijken et al.
Prediction models are used among others to inform medical decisions on interventions. Typically, individuals with high risks of adverse outcomes are advised to undergo an intervention while those at low risk are advised to refrain from it. ...
Domain Selection for Gaussian Process Data: An Application to Electrocardiogram Signals [0.03%]
高斯过程数据的领域选择及其在心电图信号中的应用
Nicolás Hernández,Gabriel Martos
Nicolás Hernández
Gaussian processes and the Kullback-Leibler divergence have been deeply studied in statistics and machine learning. This paper marries these two concepts and introduce the local Kullback-Leibler divergence to learn about intervals where two...
Model Selection for Ordinary Differential Equations: A Statistical Testing Approach [0.03%]
基于统计检验的常微分方程模型选择方法研究
Itai Dattner,Shota Gugushvili,Oleksandr Laskorunskyi
Itai Dattner
Ordinary differential equations (ODEs) are foundational tools in modeling intricate dynamics across a gamut of scientific disciplines. Yet, a possibility to represent a single phenomenon through multiple ODE models, driven by different unde...
Jiahui Feng,Kin Yau Wong,Chun Yin Lee
Jiahui Feng
The logistic regression model for a binary outcome with a continuous covariate can be expressed equivalently as a two-sample density ratio model for the covariate. Utilizing this equivalence, we study a change-point logistic regression mode...
Incompletely Observed Nonparametric Factorial Designs With Repeated Measurements: A Wild Bootstrap Approach [0.03%]
具有重复测量的不完全观察非参数因子设计：一种自助法方法
Lubna Amro,Frank Konietschke,Markus Pauly
Lubna Amro
In many life science experiments or medical studies, subjects are repeatedly observed and measurements are collected in factorial designs with multivariate data. The analysis of such multivariate data is typically based on multivariate anal...
Smoothed Estimation on Optimal Treatment Regime Under Semisupervised Setting in Randomized Trials [0.03%]
半监督设置下随机对照试验中优化治疗策略的平滑估计方法研究
Xiaoqi Jiao,Mengjiao Peng,Yong Zhou
Xiaoqi Jiao
A treatment regime refers to the process of assigning the most suitable treatment to a patient based on their observed information. However, prevailing research on treatment regimes predominantly relies on labeled data, which may lead to th...