Powerful nonparametric statistics to compare k independent ROC curves

The authors deal with the problem of comparing receiver operating characteristic (ROC) curves from independent samples. From a nonparametric approach, they propose and study three different statistics. Their asymptotic distributions are obtained and a resample plan is considered. In order to study the statistical power of the introduced statistics, a simulation study is carried out. The (observed) results suggest that, for the considered models, the new statistics are more powerful than the usually employed ones (the Venkatraman test and the usual area under the ROC curve criterion) in non-uniform dominance situations and quite good otherwise.     

Why is not design of experiments widely used by engineers in Europe?

An extensive literature review was carried out to detect why design of experiments (DoE) is not widely used among engineers in Europe. Once 16 main barriers were identified, a survey was carried out to obtain first-hand information about the significance of each. We obtained 101 responses from academics, consultants and practitioners interested in DoE. A statistical analysis of the survey is introduced, including: (a) a ranking of the barriers, (b) grouping of barriers using factorial analysis, (c) differences between characteristics of respondents. This exploratory analysis showed that the main barriers that hinder the widespread use of DoE are low managerial commitment and engineers’ general weakness in statistics. Once the barriers were classified, the most important resultant group was that related to business barriers.     

Mean-Based Iterative Procedures in Linear Models with General Errors and Grouped Data

Abstract.  We present in this paper iterative estimation procedures, using conditional expectations, to fit linear models when the distributions of the errors are general and the dependent data stem from a finite number of sources, either grouped or non-grouped with different classification criteria. We propose an initial procedure that is inspired by the expectation-maximization (EM) algorithm, although it does not agree with it. The proposed procedure avoids the nested iteration, which implicitly appears in the initial procedure and also in the EM algorithm. The stochastic asymptotic properties of the corresponding estimators are analysed.     

A THEORY OF THE POLITICALLY OPTIMAL COMMODITY TAX

A theory of the politically optimal tax is developed where tax rates are endogenous and determined by forces in the political market. The theory is used to explain the levels of alcoholic beverage taxes between states in the United States. It is shown that these rates are influenced by the ownership structure existing in the liquor industry, the consumption externalities associated with drinking, the minimum drinking age laws, the earmarking of tax revenues, the enforcement of regulations and real income.     

New critical region tables for Fisher's exact test

The best-known non-asymptotic method for comparing two independent proportions is Fisher's exact text. The usual critical region (CR) tables for this test contain one or more of the following defects:they distinguish between rows and columns; they distinguish between the alternatives H = p1 < p2 and H = p1 > p2; they assume that the error for the two-tailed test is twice that of the one-tailed test; they do not use the optimal version of the test; they do not give both CRs for one and two tails at the same time. All this results in the unnecessary duplication of the space required for the tables, the construction of tables of low-powered methods, or the need to manipulate two different tables (one for the one-tailed test, the other for the two-tailed test). This paper presents CR tables which have been obtained from the most powerful version of Fisher's exact test and which occupy the minimum space possible. The tables, which are valid for one- or two-tailed tests, have levels of significance of 10%, 5% and 1% and values for N (the total size of both samples) of less than or equal to 40. This article shows how to calculate the P value in a specific problem, using the tables as a means of partial checking and as a preliminary step to determining the exact P value.     

Mean estimation through proportion estimation

In this work a device which changes the problem of mean estimation into that of proportion estimation is proposed. The device consists of perturbing the observations. The goal of the work is the construction of conservative confidence intervals for means. Three applications are given: (1) proportion estimation in the context of cluster random sampling, (2) differences of proportions of a multinomial population and (3) variance estimation.     

A new approach to truncated regression for count data

AStA Advances in Statistical Analysis - Standard Poisson and negative binomial truncated regression models for count data include the regressors in the mean of the non-truncated distribution. In...     

Efficient generation of random vectors by using the ratio-of-uniforms method with ellipsoidal envelopes

Stochastic simulation is widely used to validate procedures and provide guidance for both theoretical and practical problems. Random variate generation is the basis of stochastic simulation. Applying the ratio-of-uniforms method to generate random vectors requires the ability to generate points uniformly in a suitable region of the space. Starting from the observation that, for many multivariate distributions, the multidimensional objective region can be covered by a hyper-ellipsoid more tightly than by a hyper-rectangle, a new algorithm to generate from multivariate distributions is proposed. Due to the computational saving it can produce, this method becomes an appealing statistical tool to generate random vectors from families of standard and nonstandard multivariate distributions. It is particularly interesting to generate from densities known up to a multiplicative constant, for example, from those arising in Bayesian computation. The proposed method is applied and its efficiency is shown for some classes of distributions.     

A clustering cure rate model with application to a sealant study

In this paper, the destructive negative binomial (DNB) cure rate model with a latent activation scheme [V. Cancho, D. Bandyopadhyay, F. Louzada, and B. Yiqi, The DNB cure rate model with a latent activation scheme, Statistical Methodology 13 (2013b), pp. 48–68] is extended to the case where the observations are grouped into clusters. Parameter estimation is performed based on the restricted maximum likelihood approach and on a Bayesian approach based on Dirichlet process priors. An application to a real data set related to a sealant study in a dentistry experiment is considered to illustrate the performance of the proposed model.