Perception,Preference, and Patriotism: An Exploratory Analysis of the 1980 Winter Olympics

This article analyzes scores given by judges of figure skating at the 1980 Winter Olympics. Judges' scores are found to be highly correlated, with little evidence of scoring along political lines. However, an analysis of variance shows a small but consistent “patriotic” bias; judges tend to give higher scores to contestants from their own country. The influence of such effects on final placings is estimated.     

Combination of multiple scores for nonparametric testing in multivariate linear regression set-up

For the problem of testing absence of x.egression under the p-variate nonparametric linear regression set-up involving m predictors, standard rank test criteria are in the form of a quadratic form in mp linear rank statistics. Different standard tests correspond to different choices of one system of scores for each variable. In this paper we propose two test criteria which are based on simultaneous choice of more than one system of scores for each variable. The criteria are obtained by applying the union-intersection technique in two different ways. It turns out that for either criterion the use of several systems of scores for each variable results in an improvement in the asymptotic power.     

Patterns of NBA team performance from 1950 to 1998

This paper examines team performance in the NBA over the last five decades. It was motivated by two previous observational studies, one of which studied the winning percentages of professional baseball teams over time, while the other examined individual player performance in the NBA. These studies considered professional sports as evolving systems, a view proposed by evolutionary biologist Stephen Jay Gould, who wrote extensively on the disappearance of .400 hitters in baseball. Gould argued that the disappearance is actually a sign of improvement in the quality of play, reflected in the reduction of variability in hitting performance. The previous studies reached similar conclusions in terms of winning percentages of baseball teams, and performance of individual players in basketball. This paper uses multivariate measures of team performance in the NBA to see if similar characteristics of evolution can be observed. The conclusion does not appear to be clearly affirmative, as in previous studies, and possible reasons for this are discussed.     

A lower bound to the measure of optimality for main effect plans in the general asymmetric factorial experiments

A design d is called D-optimal if it maximizes det(M _d ) and is called MS-optimal if it maximizes tr(M _d ) and minimizes tr[(M _d )²] among those which maximize tr(M _d ), where M _d stands for the information matrix produced from d under a given model. In this paper, we establish a lower bound for tr[(M _d )²] with respect to a main effects model, where d is an s ₁×s ₂×···×s _m levels asymmetric orthogonal array of strength at least 1. Nonisomorphic asymmetrical MS-optimal orthogonal arrays of strength 1 with N=6, 8 and 12 runs are also presented.     

An approximate entropy test for randomness

We develop an entropy-based test for randomness of binary time series of finite length. The test uses the frequencies of contiguous blocks of different lengths. A simple condition ib the block lengths and the length of the time series enables one to estimate the entropy rate for the data, and this information is used to develop a statistic to test the hypothesis of randomness. This static measures the deviation of the estimated entropy of the observed data from the theoretical maximum under the randomness hypothesis. This test offers a real alternative to the conventional runs test. Critical percentage points, based on simulations, are provided for testing the hypothesis of randomness. Power calculations using dependent data show that the proposed test has higher power against the runs test for short series, and it is similar to the runs test for long series. The test is applied to two published data sets that wree investigated by others with respect to their randomness.     

Resolution v.2 search designs

A fractional factorial design is called a resolution V.2 plan if it is capable of estimating all main effects and two-factor interaction effects, plus two three-factor interaction effects, In this paper, a necessary and sufficient condition for such a resolution V.2 plan is given, Furthermore, a new class of two-level resolution V.2 designs is proposed, We prove that the proposed design always satisfies such a necessary and sufficient condition, A comparison of run size between designs of resolutions VII and V.2 is made, It is shown that run size for design of resolution V.2 is significantly smaller.     

Lower Bounds on the Symmetric L 2-Discrepancy and Their Application

The role of uniformity measured by the symmetric L ₂-discrepancy given in Hickernell (1998 Hickernell , F. J. (1998). A generalized discrepancy and quadrature error bound. Math. Computat. 67:299–322.[Crossref], [Web of Science ®] , [Google Scholar]) has been studied in fractional factorial designs. The issue of lower bounds on the symmetric L ₂-discrepancy is crucial in the construction of uniform designs. This article reports some new lower bounds on the symmetric L ₂-discrepancy for symmetric fractional factorials and for a set of asymmetric fractional factorials. It is valuable to use these lower bounds to measure uniformity of given designs.     

A Lower Bound to the Measure of Optimality for Main Effect Plans in the Symmetric Factorial Experiments

A design d is called D-optimal if it maximizes det(M _d ), and is called MS-optimal if it maximizes tr(M _d ) and minimizes tr[(M _d )²] among those which maximize tr(M _d ), where M _d stands for the information matrix produced from d under a given model. In this article, we establish a lower bound for tr[(M _d )²] with respect to a main effects model, where d is an s-level symmetric orthogonal array of strength at least one. Non isomorphic two level MS-optimal orthogonal arrays of strength one with N = 10, 14, and 18 runs, non isomorphic three level MS-optimal orthogonal arrays of strength one with N = 6, 12, and 15 runs and non isomorphic four level MS-optimal orthogonal arrays of strength one with N = 12 runs are also presented.     

A semiparametric pseudo-score method for analysis of two-phase studies with continuous phase-I covariates

Two-phase study designs can reduce cost and other practical burdens associated with large scale epidemiologic studies by limiting ascertainment of expensive covariates to a smaller but informative sub-sample (phase-II) of the main study (phase-I). During the analysis of such studies, however, subjects who are selected at phase-I but not at phase-II, remain informative as they may have partial covariate information. A variety of semi-parametric methods now exist for incorporating such data from phase-I subjects when the covariate information can be summarized into a finite number of strata. In this article, we consider extending the pseudo-score approach proposed by Chatterjee et al. (J Am Stat Assoc 98:158–168, 2003) using a kernel smoothing approach to incorporate information on continuous phase-I covariates. Practical issues and algorithms for implementing the methods using existing software are discussed. A sandwich-type variance estimator based on the influence function representation of the pseudo-score function is proposed. Finite sample performance of the methods are studies using simulated data. Advantage of the proposed smoothing approach over alternative methods that use discretized phase-I covariate information is illustrated using two-phase data simulated within the National Wilms Tumor Study (NWTS).     

A study of uniformity pattern for extended designs

The objective of this paper is to investigate the issue of projection discrepancy for extended U-type or nearly U-type extended designs along the line of Fang and Qin (2005 Fang, K. T., and H. Qin. 2005. Uniformity pattern and related criteria for two-level factorials. Science China Series A 48:1–11.[Crossref] , [Google Scholar]) based on the centered L₂-discrepancy proposed in Hickernell (1998 Hickernell, F. J. 1998. A generalized discrepancy and quadrature error bound. Mathematics of Computation 67:299–322.[Crossref], [Web of Science ®] , [Google Scholar]). Extended designs are obtained through augmenting optimally few runs (or points) to an optimal U-type design. Lower bounds to projection discrepancy with reference to the centered L₂-discrepancy of extended designs have been obtained. Some illustrative examples are also provided.