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Interval Width (interval + width)

Distribution by Scientific Domains

Medical Sciences	40%
Mathematics and Statistics	40%

Selected Abstracts

Simultaneous prediction intervals for ARMA processes with stable innovations

JOURNAL OF FORECASTING, Issue 3 2009
John P. Nolan
Abstract We describe a method for calculating simultaneous prediction intervals for ARMA times series with heavy-tailed stable innovations. The spectral measure of the vector of prediction errors is shown to be discrete. Direct computation of high-dimensional stable probabilities is not feasible, but we show that Monte Carlo estimates of the interval width is practical. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Small proportions: what to report for confidence intervals?,

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 4 2005
Hilde Tobi
Abstract Purpose It is generally agreed that a confidence interval (CI) is usually more informative than a point estimate or p -value, but we rarely encounter small proportions with CI in the pharmacoepidemiological literature. When a CI is given it is sporadically reported, how it was calculated. This incorrectly suggests one single method to calculate CIs. To identify the method best suited for small proportions, seven approximate methods and the Clopper,Pearson Exact method to calculate CIs were compared. Methods In a simulation study for 90-, 95- and 99%CIs, with sample size 1000 and proportions ranging from 0.001 to 0.01, were evaluated systematically. Main quality criteria were coverage and interval width. The methods are illustrated using data from pharmacoepidemiology studies. Results Simulations showed that standard Wald methods have insufficient coverage probability regardless of how the desired coverage is perceived. Overall, the Exact method and the Score method with continuity correction (CC) performed best. Real life examples showed the methods to yield different results too. Conclusions For CIs for small proportions (,,,,0.01), the use of the Exact method and the Score method with CC are advocated based on this study. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Statistical Inference For Risk Difference in an Incomplete Correlated 2 × 2 Table

BIOMETRICAL JOURNAL, Issue 1 2003
Nian-Sheng Tang
Abstract In some infectious disease studies and 2-step treatment studies, 2 × 2 table with structural zero could arise in situations where it is theoretically impossible for a particular cell to contain observations or structural void is introduced by design. In this article, we propose a score test of hypotheses pertaining to the marginal and conditional probabilities in a 2 × 2 table with structural zero via the risk/rate difference measure. Score test-based confidence interval will also be outlined. We evaluate the performance of the score test and the existing likelihood ratio test. Our empirical results evince the similar and satisfactory performance of the two tests (with appropriate adjustments) in terms of coverage probability and expected interval width. Both tests consistently perform well from small- to moderate-sample designs. The score test however has the advantage that it is only undefined in one scenario while the likelihood ratio test can be undefined in many scenarios. We illustrate our method by a real example from a two-step tuberculosis skin test study. [source]

A New Method for Choosing Sample Size for Confidence Interval,Based Inferences

BIOMETRICS, Issue 3 2003
Michael R. Jiroutek
Summary. Scientists often need to test hypotheses and construct corresponding confidence intervals. In designing a study to test a particular null hypothesis, traditional methods lead to a sample size large enough to provide sufficient statistical power. In contrast, traditional methods based on constructing a confidence interval lead to a sample size likely to control the width of the interval. With either approach, a sample size so large as to waste resources or introduce ethical concerns is undesirable. This work was motivated by the concern that existing sample size methods often make it difficult for scientists to achieve their actual goals. We focus on situations which involve a fixed, unknown scalar parameter representing the true state of nature. The width of the confidence interval is defined as the difference between the (random) upper and lower bounds. An event width is said to occur if the observed confidence interval width is less than a fixed constant chosen a priori. An event validity is said to occur if the parameter of interest is contained between the observed upper and lower confidence interval bounds. An event rejection is said to occur if the confidence interval excludes the null value of the parameter. In our opinion, scientists often implicitly seek to have all three occur: width, validity, and rejection. New results illustrate that neglecting rejection or width (and less so validity) often provides a sample size with a low probability of the simultaneous occurrence of all three events. We recommend considering all three events simultaneously when choosing a criterion for determining a sample size. We provide new theoretical results for any scalar (mean) parameter in a general linear model with Gaussian errors and fixed predictors. Convenient computational forms are included, as well as numerical examples to illustrate our methods. [source]

Sonography of the normal scapholunate ligament and scapholunate joint space

JOURNAL OF CLINICAL ULTRASOUND, Issue 4 2001
James Francis Griffith FRCR
Abstract Purpose The aims of this study were to assess the visibility of the normal scapholunate ligament on sonography and to establish the normal scapholunate joint space width in the neutral position and radial and ulnar deviation. Methods Two hundred normal wrists in 100 subjects (55 men and 45 women; mean age, 40 years; range, 19,83 years) were examined with high-resolution sonography (5,12-MHz linear-array transducer). The visibility and thickness of the scapholunate ligament were recorded. The width of the scapholunate joint space, or interval, was measured in the neutral position and radial and ulnar deviation. The width of the distal radius was recorded as a comparative standard for the patients' body habitus. Results The dorsal scapholunate ligament was completely (100%) visible in 95 wrists (48%), partially (, 50%) visible in 60 (30%), barely (< 50%) visible in 15 (8%), and not visible in 30 (15%). The volar scapholunate ligament was completely visible in 13 wrists (7%), partially visible in 17 (9%), barely visible in 15 (8%), and not visible in 151 (76%). The proximal component of the ligament was not visible in any subject. Measurement of the scapholunate interval was limited by the lack of identifiable anatomic marks for reference. The mean width of the dorsal scapholunate interval was 4.2 mm (range, 2.3,6.3 mm) in the neutral position. The interval did not differ more than 2.5 mm between the left and right wrists. No predictable change in width on ulnar or radial deviation was evident. The mean scapholunate intervals and mean distal radial width were significantly wider in men than in women and on the right side than on the left side. Conclusions The dorsal scapholunate ligament is completely or partially visible in 78% of normal wrists. Its detection following injury may help to exclude the possibility of scapholunate dissociation. There is a quite wide variation in scapholunate interval widths on sonography and an unpredictable response with stress testing. The absence of a visible scapholunate ligament on sonography does not indicate injury. © 2001 John Wiley & Sons, Inc. J Clin Ultrasound 29:223,229, 2001. [source]