Sequential probability ratio test

About: Sequential probability ratio test is a research topic. Over the lifetime, 1248 publications have been published within this topic receiving 22355 citations.

Distributed sequential detection based on cell-average CFAR local tests

Abstract: In conventional distributed radar target detection, the number of accumulation returns from local sensors is typically fixed and then a decision may be made either when the information accumulated is insufficient or when it is enough excessively. In this paper, we generalize the sequential probability ratio test (SPRT) into distributed detection with local sensors using the cell-average constant false alarm rate (CA-CFAR) tests under unknown noise level. The asymptotic approximated thresholds are calculated in the proposed test. Numerical examples show that the exact error probabilities are closer to the given error probabilities, and the exact expected sample sizes (ESSs) are smaller when using the calculated thresholds than those in Wald's thresholds setting. Performance functions of the proposed method are evaluated through Fredholm integral and numerical results show its superiority compared with Wald's SPRT in performance.

Application of kappa statistics in sequential tests for family-based design

Abstract: Family-based designs are commonly used in genetic association studies to locate markers associated with diseases. It is a challenging task to collect a large enough sample size, perform a statistical test, and obtain the desired statistical power. The sequential probability ratio test (SPRT) was introduced to overcome the limited sample size problem. However, the drawback of SPRT is that, for the sake of accuracy, the test leaves many markers in a gray zone meaning “no decision”. In this article, we propose a novel approach: a sequential probability ratio test ‘plus’ (SPRT+) to reduce the number of these gray zone markers. Using simulated data, the results of SPRT+ are compared with the results of SPRT. SPRT+ shows a promising overall performance in identifying highly and moderately associated markers in the correct association region without a loss of accuracy.

Early Stopping in Experimentation with Real-time Functional Magnetic Resonance Imaging Using a Modified Sequential Probability Ratio Test

Abstract: Introduction: Functional magnetic resonance imaging (fMRI) often involves long scanning durations to ensure the associated brain activity can be detected. However, excessive experimentation can lead to many undesirable effects, such as from learning and/or fatigue effects, discomfort for the subject, excessive motion artifacts and loss of sustained attention on task. Overly long experimentation can thus have a detrimental effect on signal quality and accurate voxel activation detection. Here, we propose dynamic experimentation with real-time fMRI using a novel statistically-driven approach that invokes early stopping when sufficient statistical evidence for assessing the task-related activation is observed. Methods: Voxel-level sequential probability ratio test (SPRT) statistics based on general linear models (GLMs) were implemented on fMRI scans of a mathematical 1-back task from 12 healthy teenage subjects and 11 teenage subjects born extremely preterm (EPT). This approach is based on likelihood ratios and allows for systematic early stopping based on statistical error thresholds. We adopt a two-stage estimation approach that allows for accurate estimates of GLM parameters before stopping is considered. Early stopping performance is reported for different first stage lengths, and activation results are compared with full durations. Finally, group comparisons are conducted with both early stopped and full duration scan data. Numerical parallelization was employed to facilitate completion of computations involving a new scan within every repetition time (TR). Results: Use of SPRT demonstrates the feasibility and efficiency gains of automated early stopping, with comparable activation detection as with full protocols. Dynamic stopping of stimulus administration was achieved in around half of subjects, with typical time savings of up to 33% (4 minutes on a 12 minute scan). A group analysis produced similar patterns of activity for control subjects between early stopping and full duration scans. The EPT group, individually, demonstrated more variability in location and extent of the activations compared to the normal term control group. This was apparent in the EPT group results, reflected by fewer and smaller clusters. Conclusion: A systematic statistical approach for early stopping with real-time fMRI experimentation has been implemented. This dynamic approach has promise for reducing subject burden and fatigue effects.