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In many psychometric applications, the relationship between the mean of an outcome and a quantitative covariate is too complex to be described by simple parametric functions; instead, flexible nonlinear relationships can be incorporated…

Methodology · Statistics 2023-02-28 Boyu Ren , Stuart R. Lipsitz , Garrett M. Fitzmaurice , Roger D. Weiss

We introduce new methods of analysing time to event data via extended versions of the proportional hazards and accelerated failure time (AFT) models. In many time to event studies, the time of first observation is arbitrary, in the sense…

Methodology · Statistics 2011-02-14 Matthew Sperrin , Iain Buchan

In medical and epidemiological studies, one of the most common settings is studying the effect of a treatment on a time-to-event outcome, where the time-to-event might be censored before end of study. A common parameter of interest in such…

Methodology · Statistics 2024-02-15 Guilherme W. F. Barros , Jenny Häggström

Increasingly, medical research is dependent on data collected for non-research purposes, such as electronic health records data (EHR). EHR data and other large databases can be prone to measurement error in key exposures, and unadjusted…

Methodology · Statistics 2020-05-13 Kyunghee Han , Thomas Lumley , Bryan E. Shepherd , Pamela A. Shaw

Massive sized survival datasets are becoming increasingly prevalent with the development of the healthcare industry. Such datasets pose computational challenges unprecedented in traditional survival analysis use-cases. A popular way for…

Methodology · Statistics 2023-05-09 Nir Keret , Malka Gorfine

Application of discrete-time survival methods for continuous-time survival prediction is considered. For this purpose, a scheme for discretization of continuous-time data is proposed by considering the quantiles of the estimated event-time…

Machine Learning · Statistics 2019-10-16 Håvard Kvamme , Ørnulf Borgan

Multi-state survival analysis (MSA) uses multi-state models for the analysis of time-to-event data. In medical applications, MSA can provide insights about the complex disease progression in patients. A key challenge in MSA is the accurate…

Machine Learning · Computer Science 2022-07-13 Md Mahmudur Rahman , Sanjay Purushotham

While randomized controlled trials (RCTs) are the gold standard for estimating treatment effects in medical research, there is increasing use of and interest in using real-world data for drug development. One such use case is the…

Methodology · Statistics 2021-10-11 Devin Incerti , Michael T Bretscher , Ray Lin , Chris Harbron

This paper explores the effects of simulated moments on the performance of inference methods based on moment inequalities. Commonly used confidence sets for parameters are level sets of criterion functions whose boundary points may depend…

Econometrics · Economics 2018-04-12 Hiroaki Kaido , Jiaxuan Li , Marc Rysman

We argue that randomized controlled trials (RCTs) are special even among settings where average treatment effects are identified by a nonparametric unconfoundedness assumption. This claim follows from two results of Robins and Ritov (1997):…

Methodology · Statistics 2021-09-28 P. M. Aronow , James M. Robins , Theo Saarinen , Fredrik Sävje , Jasjeet Sekhon

Easy-to-interpret effect estimands are highly desirable in survival analysis. In the competing risks framework, one good candidate is the restricted mean time lost (RMTL). It is defined as the area under the cumulative incidence function up…

Methodology · Statistics 2024-09-13 Merle Munko , Dennis Dobler , Marc Ditzhaus

We describe a modified sequential probability ratio test that can be used to reduce the average sample size required to perform statistical hypothesis tests at specified levels of significance and power. Examples are provided for $z$ tests,…

Methodology · Statistics 2020-12-04 Sandipan Pramanik , Valen E. Johnson , Anirban Bhattacharya

Robins 1997 introduced marginal structural models (MSMs), a general class of counterfactual models for the joint effects of time-varying treatment regimes in complex longitudinal studies subject to time-varying confounding. In his work,…

Methodology · Statistics 2020-07-27 Haben Michael , Yifan Cui , Scott Lorch , Eric Tchetgen Tchetgen

We consider exact asymptotics of the minimax risk for global testing against sparse alternatives in the context of high dimensional linear regression. Our results characterize the leading order behavior of this minimax risk in several…

Statistics Theory · Mathematics 2020-03-03 Rajarshi Mukherjee , Subhabrata Sen

Interval censoring occurs when event times are only known to fall between scheduled assessments, a common design in clinical trials, epidemiology, and reliability studies. Standard right-censoring methods, such as Kaplan-Meier and Cox…

Methodology · Statistics 2025-09-04 J. T. Korley

Recently, there as been an increasing interest in the use of heavily restricted randomization designs which enforces balance on observed covariates in randomized controlled trials. However, when restrictions are strict, there is a risk that…

Methodology · Statistics 2021-10-15 Mattias Nordin , Mårten Schultzberg

Meta-analyses are commonly used to provide solid evidence across numerous studies. Traditional moment methods, such as the DerSimonian-Laird method, remain popular in spite of the availability of more accurate alternatives. While moment…

Methodology · Statistics 2024-12-06 Keisuke Hanada , Tomoyuki Sugimoto

Researchers in genetics and other life sciences commonly use permutation tests to evaluate differences between groups. Permutation tests have desirable properties, including exactness if data are exchangeable, and are applicable even when…

Computation · Statistics 2018-11-01 Brian Segal , Thomas Braun , Michael Elliott , Hui Jiang

Hazard ratios are frequently reported in time-to-event and epidemiological studies to assess treatment effects. In observational studies, the combination of propensity score weights with the Cox proportional hazards model facilitates the…

Methodology · Statistics 2024-02-14 Guilherme W. F. Barros , Jenny Häggström

Interval-censoring frequently occurs in studies of chronic diseases where disease status is inferred from intermittently collected biomarkers. Although many methods have been developed to analyze such data, they typically assume perfect…

Methodology · Statistics 2026-05-26 Yuhao Deng , Donglin Zeng , Yuanjia Wang