Doubly robust and efficient calibration of prediction sets for right-censored time-to-event outcomes [0.03%]
双稳健且有效的右删失时间事件结果预测集校准方法
Rebecca Farina,Eric Tchetgen Tchetgen,Arun Kumar Kuchibhotla
Rebecca Farina
Our objective is to construct well-calibrated prediction sets for a time-to-event outcome subject to right censoring with guaranteed coverage. Inspired by modern conformal inference, our approach avoids the need for a well-specified paramet...
Individualized dynamic latent factor model for multi-resolutional data with application to mobile health [0.03%]
一种应用于移动健康的数据多分辨率个性化动态潜在因素模型
J Zhang,F Xue,Q Xu et al.
J Zhang et al.
Mobile health has emerged as a major success for tracking individual health status, due to the popularity and power of smartphones and wearable devices. This has also brought great challenges in handling heterogeneous, multi-resolution data...
Caitrin Murphy,Eric Laber,Rhonda Merwin et al.
Caitrin Murphy et al.
Functional principal component analysis is a key tool in the study of functional data, driving both exploratory analyses and feature construction for use in formal modelling and testing procedures. However, existing methods do not apply whe...
Yonghoon Lee,Edgar Dobriban,Eric J Tchetgen Tchetgen
Yonghoon Lee
We consider the problem of comparing a reference distribution with several other distributions. Given a sample from both the reference and the comparison groups, we aim to identify the comparison groups whose distributions differ from that ...
Sequential Gibbs posteriors with applications to principal component analysis [0.03%]
基于顺序Gibbs后验的主成分分析方法及其应用
Steven Winter,Omar Melikechi,David B Dunson
Steven Winter
Gibbs posteriors are proportional to a prior distribution multiplied by an exponentiated loss function, with a key tuning parameter that weights the information in the loss relative to the prior and provides control of posterior uncertainty...
Comparing causal parameters with many treatments and positivity violations [0.03%]
多种处理情况下的因果参数比较及阳性违反问题
A McClean,Y Li,S Bae et al.
A McClean et al.
Comparing outcomes across treatments is essential in medicine and public policy. To do so, researchers typically estimate a set of parameters, possibly counterfactual, each targeting adifferent treatment. Treatment-specific means are common...
Leveraging External Data for Testing Experimental Therapies with Biomarker Interactions in Randomized Clinical Trials [0.03%]
利用外部数据在随机临床试验中测试具有生物标志物相互作用的实验性疗法
B Ren,F Ferrari,S Fortini et al.
B Ren et al.
In oncology the efficacy of novel therapeutics often differs across patient subgroups, and these variations are difficult to predict during the initial phases of the drug development process. The relation between the power of randomized cli...
Ting-Hsuan Chang,Zijian Guo,Daniel Malinsky
Ting-Hsuan Chang
Algorithms for constraint-based causal discovery select graphical causal models among a space of possible candidates (e.g., all directed acyclic graphs) by executing a sequence of conditional independence tests. These may be used to inform ...
Michael W Robbins,Lane Burgette
Michael W Robbins
Resampling techniques have become increasingly popular for estimation of uncertainty. However, data are often fraught with missing values that are commonly imputed to facilitate analysis. This article addresses the issue of using resampling...
On the asymptotic validity of confidence sets for linear functionals of solutions to integral equations [0.03%]
积分方程解的线性泛函的置信集的渐近有效性的检验
E Smucler,J M Robins,A Rotnitzky
E Smucler
This paper examines the construction of confidence sets for parameters defined as linear functionals of a function of [Formula: see text] and [Formula: see text] whose conditional mean given [Formula: see text] and [Formula: see text] equal...