Sequential analysis
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Sequential Analysis: Hypothesis Testing and Changepoint Detection Open
Sequential Analysis: Hypothesis Testing and Changepoint Detection systematically develops the theory of sequential hypothesis testing and quickest changepoint detection. It also describes important applications in which theoretical results…
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Sequential Selection Procedures and False Discovery Rate Control Open
Summary We consider a multiple-hypothesis testing setting where the hypotheses are ordered and one is only permitted to reject an initial contiguous block H1,…,Hk of hypotheses. A rejection rule in this setting amounts to a procedure for c…
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A Randomized Sequential Procedure to Determine the Number of Factors Open
This article proposes a procedure to estimate the number of common factors k in a static approximate factor model. The building block of the analysis is the fact that the first k eigenvalues of the covariance matrix of the data diverge, wh…
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Asymptotically Optimal Anomaly Detection via Sequential Testing Open
Sequential detection of independent anomalous processes among K processes is\nconsidered. At each time, only M processes can be observed, and the\nobservations from each chosen process follow two different distributions,\ndepending on whet…
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Increasing efficiency of preclinical research by group sequential designs Open
Despite the potential benefits of sequential designs, studies evaluating treatments or experimental manipulations in preclinical experimental biomedicine almost exclusively use classical block designs. Our aim with this article is to bring…
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A Multi-Source Adaptive Platform Design for Testing Sequential Combinatorial Therapeutic Strategies Open
Summary Traditional paradigms for clinical translation are challenged in settings where multiple contemporaneous therapeutic strategies have been identified as potentially beneficial. Platform trials have emerged as an approach for sequent…
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A robust pooled testing approach to expand COVID-19 screening capacity Open
Limited testing capacity for COVID-19 has hampered the pandemic response. Pooling is a testing method wherein samples from specimens (e.g., swabs) from multiple subjects are combined into a pool and screened with a single test. If the pool…
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A supermartingale approach to Gaussian process based sequential design of experiments Open
Gaussian process (GP) models have become a well-established frameworkfor the\nadaptive design of costly experiments, and notably of computerexperiments.\nGP-based sequential designs have been found practicallyefficient for various\nobjecti…
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Sequential improvement for robust optimization using an uncertainty measure for radial basis functions Open
The performance of the sequential metamodel based optimization procedure depends strongly on the chosen building blocks for the algorithm, such as the used metamodeling method and sequential improvement criterion. In this study, the effect…
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Using Bayesian adaptive designs to improve phase III trials: a respiratory care example Open
OSCAR Trial registration ISRCTN, ISRCTN10416500 . Retrospectively registered 13 June 2007.
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Using prior parameter knowledge in <span>model‐based</span> design of experiments for pharmaceutical production Open
Sequential model‐based design of experiments (MBDoE) uses information from previous experiments to select new experimental conditions. Computation of MBDoE objective functions can be impossible due to a noninvertible Fisher information mat…
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Control of Type I Error Rates in Bayesian Sequential Designs Open
Bayesian approaches to phase II clinical trial designs are usually based on the posterior distribution of the parameter of interest and calibration of certain threshold for decision making. If the posterior probability is computed and asse…
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NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation Open
Test-time adaptation (TTA) is an emerging paradigm that addresses distributional shifts between training and testing phases without additional data acquisition or labeling cost; only unlabeled test data streams are used for continual model…
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Multi‐arm group sequential designs with a simultaneous stopping rule Open
Multi-arm group sequential clinical trials are efficient designs to compare multiple treatments to a control. They allow one to test for treatment effects already in interim analyses and can have a lower average sample number than fixed sa…
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Continuous versus group sequential analysis for post‐market drug and vaccine safety surveillance Open
Summary The use of sequential statistical analysis for post‐market drug safety surveillance is quickly emerging. Both continuous and group sequential analysis have been used, but consensus is lacking as to when to use which approach. We co…
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Beyond the E-Value: Stratified Statistics for Protein Domain Prediction Open
E-values have been the dominant statistic for protein sequence analysis for the past two decades: from identifying statistically significant local sequence alignments to evaluating matches to hidden Markov models describing protein domain …
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Multiple testing procedures for adaptive enrichment designs: combining group sequential and reallocation approaches Open
Adaptive enrichment designs involve preplanned rules for modifying enrollment criteria based on accrued data in an ongoing trial. For example, enrollment of a subpopulation where there is sufficient evidence of treatment efficacy, futility…
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Searching for Anomalies Over Composite Hypotheses Open
The problem of detecting anomalies in multiple processes is considered. We\nconsider a composite hypothesis case, in which the measurements drawn when\nobserving a process follow a common distribution with an unknown parameter\n(vector), w…
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Sequential Bayesian Design for Accelerated Life Tests Open
Most of the recently developed methods on optimum planning for accelerated life tests (ALT) involve “guessing” values of parameters to be estimated, and substituting such guesses in the proposed solution to obtain the final testing plan. I…
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Sequential prevalence estimation with pooling and continuous test outcomes Open
Prevalence estimation is crucial for controlling the spread of infections and diseases and for planning of health care services. Prevalence estimation is typically conducted via pooled, or group, testing due to limited testing budgets. We …
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Sequential biases in accumulating evidence Open
Whilst it is common in clinical trials to use the results of tests at one phase to decide whether to continue to the next phase and to subsequently design the next phase, we show that this can lead to biased results in evidence synthesis. …
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Molecular Testing Strategies for Pulmonary Adenocarcinoma: An Optimal Approach With Cost Analysis Open
Context.— Molecular analysis of lung adenocarcinoma for therapeutically important genes is standard of practice, with multiple professional organizations recommending testing of all adenocarcinomas for mutations in EGFR, ALK, and ROS1. Som…
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Design and Analysis of Optimal and Minimax Robust Sequential Hypothesis Tests Open
In this dissertation a framework for the design and analysis of optimal and minimax robust sequential hypothesis tests is developed. It provides a coherent theory as well as algorithms for the implementation of optimal and minimax robust s…
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Bayesian Sequential Experimental Design for Fatigue Tests Open
A Bayesian sequential experimental design for fatigue testing was implemented on the basis on D-optimality and a non-linear continuous damage model. The design accounts for the whole range of testing levels.
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Noisy Adaptive Group Testing using Bayesian Sequential Experimental Design Open
When the infection prevalence of a disease is low, Dorfman showed 80 years ago that testing groups of people can prove more efficient than testing people individually. Our goal in this paper is to propose new group testing algorithms that …
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Sequential testing of a Wiener process with costly observations Open
We consider the sequential testing of two simple hypotheses for the drift of a Brownian motion when each observation of the underlying process is associated with a positive cost. In this setting where continuous monitoring of the underlyin…
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Sequential tests of multiple hypotheses controlling false discovery and nondiscovery rates Open
We propose a general and flexible procedure for testing multiple hypotheses about sequential (or streaming) data that simultaneously controls both the false discovery rate (FDR) and false nondiscovery rate (FNR) under minimal assumptions a…
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Sequential experimental design for predator–prey functional response experiments Open
Understanding functional response within a predator–prey dynamic is a cornerstone for many quantitative ecological studies. Over the past 60 years, the methodology for modelling functional response has gradually transitioned from the class…
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Estimating design operating characteristics in Bayesian adaptive clinical trials Open
Bayesian adaptive designs have gained popularity in all phases of clinical trials with numerous new developments in the past few decades. During the COVID‐19 pandemic, the need to establish evidence for the effectiveness of vaccines, thera…
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Optimal Sequential Diagnostic Strategy Generation Considering Test Placement Cost for Multimode Systems Open
Sequential fault diagnosis is an approach that realizes fault isolation by executing the optimal test step by step. The strategy used, i.e., the sequential diagnostic strategy, has great influence on diagnostic accuracy and cost. Optimal s…