The construction of data to reflect the research objective,and how randomisation tests make such data usable

When comparing the central values of two independent groups, should a t-test be performed, or should the observations be transformed into their ranks and a Wilcoxon-Mann-Whitney test performed? This paper argues that neither should automatically be chosen. Instead, provided that software for conducting randomisation tests is available, the chief concern should be with obtaining data values that are a good reflection of scientific reality and appropriate to the objective of the research; if necessary, the data values should be transformed so that this is so. The subsequent use of a randomisation (permutation) test will mean that failure of the transformed data values to satisfy assumptions such as normality and equality of variances will not be of concern.     

A simple condition for the multivariate CLT and the attraction to the Gaussian of Lévy processes at long and short times

We show that a necessary and sufficient condition for the sum of iid random vectors to converge (under appropriate centering and scaling) to a multivariate Gaussian distribution is that the truncated second moment matrix is slowly varying at infinity. This is more natural than the standard conditions, and allows for the possibility that the limiting Gaussian distribution is degenerate (so long as it is not concentrated at a point). We also give necessary and sufficient conditions for a d-dimensional Lévy process to converge (under appropriate centering and scaling) to a multivariate Gaussian distribution as time approaches zero or infinity.     

On robustness of the Shiryaev–Roberts change-point detection procedure under parameter misspecification in the post-change distribution

The gist of the quickest change-point detection problem is to detect the presence of a change in the statistical behavior of a series of sequentially made observations, and do so in an optimal detection-speed-versus-“false-positive”-risk manner. When optimality is understood either in the generalized Bayesian sense or as defined in Shiryaev's multi-cyclic setup, the so-called Shiryaev–Roberts (SR) detection procedure is known to be the “best one can do”, provided, however, that the observations’ pre- and post-change distributions are both fully specified. We consider a more realistic setup, viz. one where the post-change distribution is assumed known only up to a parameter, so that the latter may be misspecified. The question of interest is the sensitivity (or robustness) of the otherwise “best” SR procedure with respect to a possible misspecification of the post-change distribution parameter. To answer this question, we provide a case study where, in a specific Gaussian scenario, we allow the SR procedure to be “out of tune” in the way of the post-change distribution parameter, and numerically assess the effect of the “mistuning” on Shiryaev's (multi-cyclic) Stationary Average Detection Delay delivered by the SR procedure. The comprehensive quantitative robustness characterization of the SR procedure obtained in the study can be used to develop the respective theory as well as to provide a rational for practical design of the SR procedure. The overall qualitative conclusion of the study is an expected one: the SR procedure is less (more) robust for less (more) contrast changes and for lower (higher) levels of the false alarm risk.     

Least significant spacing for ‘one versus the rest’ normal populations

Consider sample means from k(≥2) normal populations where the variances and sample sizes are equal. The problem is to find the ‘least significant difference’ or ‘spacing’ (LSS) between the two largest means, so that if an observed spacing is larger we have confidence 1 - α that the population with largest sample mean also has the largest population mean.

When the variance is known it is shown that the maximum LSS occurs when k = 2, provided a < .2723. In other words, for any value of k we may use the usual (one-tailed) least significant difference to demonstrate that one population has a population mean greater than (or equal to) the rest.

When the variance is estimated bounds are obtained for the confidence which indicate that this last result is approximately correct.     

TESTING FOR CONTINUOUS LOCAL MARTINGALES USING THE CROSSING TREE

We present statistical tests for the continuous martingale hypothesis; that is, for whether an observed process is a continuous local martingale, or equivalently a continuous time‐changed Brownian motion. Our technique is based on the concept of the crossing tree. Simulation experiments are used to assess the power of the tests, which is generally higher than that of recently proposed tests using the estimated quadratic variation (i.e. realized volatility). In particular, the crossing tree shows significantly higher power with shorter data sets. We then show results from applying the methodology to five high‐frequency currency exchange rate data sets from 2003. For four of them we show that at small time‐scales (less than 15 minutes or so) the continuous martingale hypothesis is rejected, but not so at larger time‐scales. For the fifth, the hypothesis is rejected at small time‐scales and at some moderate time‐scales, but not all.     

Two-tailed asymptotic inferences for a proportion

This paper evaluates 29 methods for obtaining a two-sided confidence interval for a binomial proportion (16 of which are new proposals) and comes to the conclusion that: Wilson's classic method is only optimal for a confidence of 99%, although generally it can be applied when n≥50; for a confidence of 95% or 90%, the optimal method is the one based on the arcsine transformation (when this is applied to the data incremented by 0.5), which behaves in a very similar manner to Jeffreys’ Bayesian method. A simpler option, though not so good as those just mentioned, is the classic-adjusted Wald method of Agresti and Coull.     

Renovating inverval-censored responses

In this note we provide a general framework for describing interval-censored samples including estimation of the magnitude and rank positions of data that have been interval-censored so as to counteract the effect of censoring. This process of sample adjustment, or renovation, allows samples to be compared graphically, using diagrams (such as boxplots) which are based on ranks. The renovation process is based on Buckley-James regression estimators for linear regression with censored data.     

A Novel Estimation Approach for Mixture Transition Distribution Model in High-Order Markov Chains

A transformation is proposed to convert the nonlinear constraints of the parameters in the mixture transition distribution (MTD) model into box-constraints. The proposed transformation removes the difficulties associated with the maximum likelihood estimation (MLE) process in the MTD modeling so that the MLEs of the parameters can be easily obtained via a hybrid algorithm from the evolutionary algorithms and/or quasi-Newton algorithms for global optimization. Simulation studies are conducted to demonstrate MTD modeling by the proposed novel approach through a global search algorithm in R environment. Finally, the proposed approach is used for the MTD modelings of three real data sets.     

The Robustness of Common Measures of 2×2 Association to Bias Due to Misclassifications

The strength of association between two dichotomous characteristics A and B can be measured in many ways. All of these statistics are biased when there is misclassification, and all are prevalence dependent whether or not their population values are. Measures lacking fixed endpoints for random and perfect association, such as sensitivity, specificity, risk ratios, and odds ratio, have a bias either so unpredictable or so large that the observable and true measures of association may bear little resemblance to each other. Reexpressions of these measures that fix the endpoints and other measures with fixed endpoints, such as kappa, phi, gamma, risk difference, and attributable risk, produce attenuated estimates of their true values. Disattenuating such estimators is possible using test—retest data.     

Geodesic Lagrangian Monte Carlo over the space of positive definite matrices: with application to Bayesian spectral density estimation

We present geodesic Lagrangian Monte Carlo, an extension of Hamiltonian Monte Carlo for sampling from posterior distributions defined on general Riemannian manifolds. We apply this new algorithm to Bayesian inference on symmetric or Hermitian positive definite (PD) matrices. To do so, we exploit the Riemannian structure induced by Cartan's canonical metric. The geodesics that correspond to this metric are available in closed-form and – within the context of Lagrangian Monte Carlo – provide a principled way to travel around the space of PD matrices. Our method improves Bayesian inference on such matrices by allowing for a broad range of priors, so we are not limited to conjugate priors only. In the context of spectral density estimation, we use the (non-conjugate) complex reference prior as an example modelling option made available by the algorithm. Results based on simulated and real-world multivariate time series are presented in this context, and future directions are outlined.     

EDF tests of goodness of fit for transform-both-sides models

Very often in regression analysis, a particular functional form connecting known covariates and unknown parameters is either suggested by previous work or demanded by theoretical considerations so that the deterministic part of the responses has a known form. However, the underlying error structure is often less well understood. In this case, the transform-both-sides (TBS) models are appropriate. In this paper we generalize the usual TBS models and develop tests to assess goodness of fit when fitting TBS or GTBS models. Parameter estimation is discussed, and tests based on the Cramér-von Mises statistic and the Anderson-Darling statistic are presented with a table suitable for finite-sample applications.     

Tools of the Serials Trade

Abstract

Many university libraries are facing budget flat-lines or reductions. While finding ways to reduce or reallocate a libraries budget is not new, the planning processes within this article merit consideration, especially for small and medium-sized libraries. Librarians must build and maintain strong relationships with constituencies and be forthright in sharing information so that joint decisions can be made. Developing a strategic plan to address the budget shortfalls and having an effective communication plan are keys to the successful outcome of any budget reduction or reallocation process. This article details the strategies and implementation of one university library.     

Analysis of progression-free survival in oncology trials: some common statistical issues

With the advent of ever more effective second and third line cancer treatments and the growing use of 'crossover' trial designs in oncology, in which patients switch to the alternate randomized treatment upon disease progression, progression-free survival (PFS) is an increasingly important endpoint in oncologic drug development. However, several concerns exist regarding the use of PFS as a basis to compare treatments. Unlike survival, the exact time of progression is unknown, so progression times might be over-estimated and, consequently, bias may be introduced when comparing treatments. Further, it is not uncommon for randomized therapy to be stopped prior to progression being documented due to toxicity or the initiation of additional anti-cancer therapy; in such cases patients are frequently not followed further for progression and, consequently, are right-censored in the analysis. This article reviews these issues and concludes that concerns relating to the exact timing of progression are generally overstated, with analysis techniques and simple alternative endpoints available to either remove bias entirely or at least provide reassurance via supportive analyses that bias is not present. Further, it is concluded that the regularly recommended manoeuvre to censor PFS time at dropout due to toxicity or upon the initiation of additional anti-cancer therapy is likely to favour the more toxic, less efficacious treatment and so should be avoided whenever possible.     

Efficiency of generalized estimating equations for binary responses

Summary.  Using standard correlation bounds, we show that in generalized estimation equations (GEEs) the so-called 'working correlation matrix' R ( α ) for analysing binary data cannot in general be the true correlation matrix of the data. Methods for estimating the correlation param-eter in current GEE software for binary responses disregard these bounds. To show that the GEE applied on binary data has high efficiency, we use a multivariate binary model so that the covariance matrix from estimating equation theory can be compared with the inverse Fisher information matrix. But R ( α ) should be viewed as the weight matrix, and it should not be confused with the correlation matrix of the binary responses. We also do a comparison with more general weighted estimating equations by using a matrix Cauchy–Schwarz inequality. Our analysis leads to simple rules for the choice of α in an exchangeable or autoregressive AR(1) weight matrix R ( α ), based on the strength of dependence between the binary variables. An example is given to illustrate the assessment of dependence and choice of α .     

A critique of recent methods for computing the distribution of the Durbin-Watson and other invariant test statistics

In recent papers Ansley, Kohn and Shively (SAK, 1990; AKS, 1992; KSA, 1993) have proposed methods for evaluating the null distribution of the Durbin-Watson and related statistics more rapidly than by the methods of Davies (1980) or Farebrother (1980, 1990). In this paper we discuss several problems concerning the numerical accuracy of these new procedures and recommend that practitioners intending to use them should do so with caution.     

Hyper-Graeco-Latin Squares and Fractional Factorial Designs

A Latin square of order s is an arrangement of the s letters in an s × s square so that every letter appears exactly once in every row and exactly once in every column. Copeland and Nelson (2000) used two examples to show that a Latin square can be chosen such that it corresponds to a fractional factorial design. In this article, we are going to study this topic more precisely. Furthermore, we will explore the relationship between fractional factorial designs and hyper-Graeco-Latin squares in general, where s is a prime or a power of a prime.     

Inferences from DNA data: population histories, evolutionary processes and forensic match probabilities

Summary. We develop a flexible class of Metropolis–Hastings algorithms for drawing inferences about population histories and mutation rates from deoxyribonucleic acid (DNA) sequence data. Match probabilities for use in forensic identification are also obtained, which is particularly useful for mitochondrial DNA profiles. Our data augmentation approach, in which the ancestral DNA data are inferred at each node of the genealogical tree, simplifies likelihood calculations and permits a wide class of mutation models to be employed, so that many different types of DNA sequence data can be analysed within our framework. Moreover, simpler likelihood calculations imply greater freedom for generating tree proposals, so that algorithms with good mixing properties can be implemented. We incorporate the effects of demography by means of simple mechanisms for changes in population size and structure, and we estimate the corresponding demographic parameters, but we do not here allow for the effects of either recombination or selection. We illustrate our methods by application to four human DNA data sets, consisting of DNA sequences, short tandem repeat loci, single-nucleotide polymorphism sites and insertion sites. Two of the data sets are drawn from the male-specific Y-chromosome, one from maternally inherited mitochondrial DNA and one from the β -globin locus on chromosome 11.     

An approximation to cluster size distribution of two Gaussian random fields conjunction with application to FMRI data

In brain mapping, the regions of the brain that are ‘activated’ by a task or external stimulus are detected by thresholding an image of test statistics. Often the experiment is repeated on several different subjects or for several different stimuli on the same subject, and the researcher is interested in the common points in the brain where ‘activation’ occurs in all test statistic images. The conjunction is thus defined as those points in the brain that show ‘activation’ in all images. We are interested in which parts of the conjunction are noise, and which show true activation in all test statistic images. We would expect truly activated regions to be larger than usual, so our test statistic is based on the volume of clusters (connected components) of the conjunction. Our main result is an approximate P-value for this in the case of the conjunction of two Gaussian test statistic images. The results are applied to a functional magnetic resonance experiment in pain perception.     

Role of statistics in quality and productivity improvement

The role of statistics in quality and productivity improvement depends on certain philosophical issues that the author believes have been inadequately addressed. Three such issues are as follows: (1) what is the role of statistics in the process of investigation and discovery; (2) how can we extrapolate results from the particular to the general; and (3) how can we evaluate possible management changes so that they truly benefit an organization? Therefore, statistical methods appropriate to investigation and discovery are discussed as distinct from those appropriate to the testing of an already discovered solution. It is shown how the manner in which the tentative solution has been arrived at determines the assurance with which experimental conclusions can be extrapolated to the application in mind. Whether or not statistical methods and training can have any impact depends on the system of management. A vector representation which can help predict the consequences of changes in management strategy is discussed. This can help to realign policies so that members of an organization can better work together for the benefit of the organization.     

The “Green” and “Gold” Roads to Open Access: The Case for Mixing and Matching

Abstract

Recent discussions on Open Access (OA) have tended to treat OA journals and self-archiving as two distinct routes. Some supporters of self-archiving even suggest that it alone can bring about full Open Access to the world's scientific literature. In this paper, it is argued that each route actually corresponds to a phase in the movement toward Open Access; that the mere fact of self-archiving is not enough; that providing some branding ability to the repositories is needed. However, doing so will eventually bring about the creation of overlay (or database) journals. The two roads, therefore, will merge to create a mature OA landscape.