Microarray technology has produced a huge body of time-course gene expression data and will continue to produce more. Such gene expression data has been proved useful in genomic disease diagnosis and drug design. The challenge is how to uncover useful information from such data by proper analysis methods such as significance analysis and clustering analysis. Many statistic-based significance an...

OBJECTIVE This paper describes a new class of space-time scan statistics designed for rapid detection of emerging disease clusters. We evaluate these methods on the task of prospective disease surveillance, and show that our methods consistently outperform the standard space-time scan statistic approach. BACKGROUND The space-time scan statistic [1] is a powerful statistical tool for prospective...

Medicaid spending growth has varied greatly over time. This article uses financial and statistical data to trace the history of Medicaid spending in relation to some of the major factors that have influenced its growth over the years. Periods of varying growth are divided into eight "eras," ranging from program startup in 1966 through the post-welfare reform period. Average expenditure and enro...

Items such as physical exam findings, radiographic interpretations, or other diagnostic tests often rely on some degree of subjective interpretation by observers. Studies that measure the agreement between two or more observers should include a statistic that takes into account the fact that observers will sometimes agree or disagree simply by chance. The kappa statistic (or kappa coefficient) ...

This paper proposes a robustification of the test statistic of Aït-Sahalia and Jacod (2009b) for the presence of market microstructure noise in high frequency data, based on the pre-averaging method of Jacod et al. (2010). We show that the robustified statistic restores the test’s discriminating power between jumps and no jumps despite the presence of market microstructure noise in the data. © ...

Large-scale comparison of the similarities between two biological sequences is a major issue in computational biology; a fast method, the D(2) statistic, relies on the comparison of the k-tuple content for both sequences. Although it has been known for some years that the D(2) statistic is not suitable for this task, as it tends to be dominated by single-sequence noise, to date no suitable adju...

In many randomized clinical trials with repeated measures of a response variable one anticipates a linear divergence over time in the difference between treatments. This paper explores how to make an efficient choice of analysis based on individual patient summary statistics. With the objective of estimating the mean rate of treatment divergence the simplest choice of summary statistic is the r...

The statistical method in a comparative study in which the standard treatment is theoretically or practically superior to the others has been investigated for a matched-pairs design. We derived this statistical method from one based on the maximum likelihood and score methods. Here we have shown that the score test statistic is algebraically the same as the statistic from the maximum likelihood...

Current national expenditure series in the health sector focus predominantly on spending for medical services. However, as the percentage of elderly individuals grows, national policy makers will increasingly require an expenditure series which includes combined expenditure for social care as well as medical expenditures. In one country, Sweden, national policy makers have begun to relate polic...

The U-statistic elegantly and usefully generalizes the notion of a sample mean. Typical examples include (i) sample mean: h(x1, x2) = 12 (x1 + x2); (ii) sample variance: h(x1, x2) = 12 (x1 − x2); (iii) Gini’s mean difference: h(x1, x2) = |x1 − x2|; (iv) one-sample Wilcoxon’s statistic: h(x1, x2) = 1(x1 + x2 ≤ 0). The non-degenerate U-statistic shares many limiting properties with the sample mea...