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Background: Screening trials require large sample sizes and long time-horizons to demonstrate mortality reductions. We recently proposed increasing statistical power by testing stored control-arm specimens, called the Intended Effect (IE)…

Applications · Statistics 2024-11-11 Hormuzd A. Katki , Li C. Cheung

This paper introduces a new method for change detection in psychometric studies based on the recently introduced pseudo Score statistic, for which the sampling distribution under the alternative hypothesis has been determined. Our approach…

Methodology · Statistics 2024-08-09 Nicoletta D'Angelo

Nonparametric two sample testing deals with the question of consistently deciding if two distributions are different, given samples from both, without making any parametric assumptions about the form of the distributions. The current…

Statistics Theory · Mathematics 2014-11-25 Aaditya Ramdas , Sashank J. Reddi , Barnabas Poczos , Aarti Singh , Larry Wasserman

For biological experiments aiming at calibrating models with unknown parameters, a good experimental design is crucial, especially for those subject to various constraints, such as financial limitations, time consumption and physical…

Applications · Statistics 2014-07-22 Xiao Lin , Gabriel Terejanu

For randomized controlled trials to be conclusive, it is important to set the target sample size accurately at the design stage. Comparing two normal populations, the sample size calculation requires specification of the variance other than…

Methodology · Statistics 2026-02-04 Hirotada Maeda , Satoshi Hattori , Tim Friede

Simulation studies are computer experiments that involve creating data by pseudorandom sampling. The key strength of simulation studies is the ability to understand the behaviour of statistical methods because some 'truth' (usually some…

Methodology · Statistics 2019-01-18 Tim P Morris , Ian R White , Michael J Crowther

Recent advances in steady-state analysis of power systems have introduced the equivalent split-circuit approach and corresponding continuation methods that can reliably find the correct physical solution of large-scale power system…

Systems and Control · Computer Science 2018-04-24 Martin R. Wagner , Amritanshu Pandey , Marko Jereminov , Larry Pileggi

Deep neural two-sample tests have recently shown strong power for detecting distributional differences between groups, yet their black-box nature limits interpretability and practical adoption in biomedical analysis. Moreover, most existing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Masoumeh Javanbakhat , Piotr Komorowski , Dilyara Bareeva , Wei-Chang Lai , Wojciech Samek , Christoph Lippert

A common feature of many recent trials evaluating the effects of immunotherapy on survival is that non-proportional hazards can be anticipated at the design stage. This raises the possibility to use a statistical method tailored towards…

Applications · Statistics 2021-08-27 Dominic Magirr , José L. Jiménez

A new method based on the rejection sampling for finding statistical tests is proposed. This method is conceptually intuitive, easy to implement, and applicable for arbitrary dimension. To illustrate its potential applicability, three…

Methodology · Statistics 2026-03-11 Markku Kuismin

Data depth has emerged as an invaluable nonparametric measure for the ranking of multivariate samples. The main contribution of depth-based two-sample comparisons is the introduction of the Q statistic (Liu and Singh, 1993), a quality…

Methodology · Statistics 2024-08-21 Yiting Chen , Min Gao , Wei Lin , Andrew Jirasek , Kirsty Milligan , Xiaoping Shi

Before embarking on data collection, researchers typically compute how many individual observations they should do. This is vital for doing studies with sufficient statistical power, and often a cornerstone in study pre-registrations and…

Methodology · Statistics 2023-09-06 Edwin S Dalmaijer

Quality by design in pharmaceutical manufacturing hinges on computational methods and tools that are capable of accurate quantitative prediction of the design space. This paper investigates Bayesian approaches to design space…

We consider the estimation of densities in multiple subpopulations, where the available sample size in each subpopulation greatly varies. This problem occurs in epidemiology, for example, where different diseases may share similar…

Methodology · Statistics 2021-09-15 Jiaming Qiu , Xiongtao Dai , Zhengyuan Zhu

Restricted mean survival time (RMST) is gaining attention as a measure to quantify the treatment effect on survival outcomes in randomized clinical trials. Several methods to determine sample size based on the RMST-based tests have been…

Methodology · Statistics 2022-12-19 Satoshi Hattori , Hajime Uno

Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula…

Methodology · Statistics 2014-06-12 Elisa Perrone , Werner G. Müller

Many applications of machine learning methods involve an iterative protocol in which data are collected, a model is trained, and then outputs of that model are used to choose what data to consider next. For example, one data-driven approach…

Machine Learning · Computer Science 2025-04-07 Clara Fannjiang , Stephen Bates , Anastasios N. Angelopoulos , Jennifer Listgarten , Michael I. Jordan

Recently, numerous pharmaceutical sponsors have expressed a great deal of interest in the development of biosimilars, which requires clinical trials to demonstrate the equivalence of pharmacokinetics (PK) and clinical efficacy.…

Applications · Statistics 2017-05-16 Ryuji Uozumi , Chikuma Hamada

We propose new tests for assessing whether covariates in a treatment group and matched control group are balanced in observational studies. The tests exhibit high power under a wide range of multivariate alternatives, some of which existing…

Methodology · Statistics 2019-02-28 Hao Chen , Dylan S. Small

We present a new experimental design procedure that divides a set of experimental units into two groups so that the two groups are balanced on a prespecified set of covariates and being almost as random as complete randomization. Under…

Statistics Theory · Mathematics 2016-12-08 Abba M. Krieger , David Azriel , Adam Kapelner
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