Gender Differences in Publication among University Professors in Canada*

Cet article analyse un important sondage à l'échelle canadienne et aborde la probématique de la productivité: pourquoi les professeures d'université publient‐elles moins que leurs collégues hommes ? Les résultats montrent que, dans l'ensemble, les femmes ont publié moins que les hommes — et ce, de manière significative —, à la fois durant leur carrière et au cours des trois années qui ont précédé le sondage. Cependant, des analyses multivariables révèlent que des différences s'avèrent plus prononcées dans les données touchant la carrière que dans celles de la courte période. La plus grande différence entre les hommes et les femmes a trait au fait de publier dans une revue à comité de lecture ou sans, et s'applique à toute leur carrière. Enfin, des différences se laissent expliquer par des différences de rang, d'années depuis l'obtention du doctorat, la discipline, le type d'université ainsi que le temps consacré a la recherche. Des problèmes d'évaluation des prédicteurs de la productivité en recherche sont discutés. This paper analyses a large Canadian national survey of professors and tackles the “productivity puzzle” as to why female scientists publish less than male scientists. Results show that, in aggregate, Canadian female professors have published significantly less than their male counterparts, both over their lifetimes and during the three years before the survey. However, multivariate analyses reveal that gender differences in publication are more pronounced in the lifetime data than in the data for the shorter period. Much of the difference in publication between men and women of the academy is in refereed and non‐refereed articles and reports over their career. Finally, gender differences in publication are largely accounted for by differences in rank, years since PhD, discipline, type of university and time set aside for research. Problems of assessing predictors of research productivity are discussed.     

Maximum likelihood estimation of sensitive proportion using repeated randomized response techniques

Randomized response techniques are designed to obtain usable data on sensitive issues while protecting the privacy of individuals. In this paper, based on repeating the randomized response technique, a new technique called repeated randomized response is introduced to increase the protection of privacy and efficiency of estimator for proportion of sensitive attribute. By using this technique, the proportion of academic cheating is estimated among students of Shahid Chamran University of Ahvaz, Ahvaz, Iran.     

The inverse 1-center problem on trees with variable edge lengths under Chebyshev norm and Hamming distance

This paper addresses the problem of modifying the edge lengths of a tree in minimum total cost such that a prespecified vertex becomes the 1-center of the perturbed tree. This problem is called the inverse 1-center problem on trees. We focus on the problem under Chebyshev norm and Hamming distance. From special properties of the objective functions, we can develop combinatorial algorithms to solve the problem. Precisely, if there does not exist any vertex coinciding with the prespecified vertex during the modification of edge lengths, the problem under Chebyshev norm or bottleneck Hamming distance is solvable in \(O(n\log n)\) time, where \(n+1\) is the number of vertices of the tree. Dropping this condition, the problem can be solved in \(O(n^{2})\) time.     

Goodness-of-fit tests for progressively Type-II censored data from location–scale distributions

In this article, we propose several goodness-of-fit methods for location–scale families of distributions under progressively Type-II censored data. The new tests are based on order statistics and sample spacings. We assess the performance of the proposed tests for the normal and Gumbel models against several alternatives by means of Monte Carlo simulations. It has been observed that the proposed tests are quite powerful in comparison with an existing goodness-of-fit test proposed for progressively Type-II censored data by Balakrishnan et al. [Goodness-of-fit tests based on spacings for progressively Type-II censored data from a general location–scale distribution, IEEE Trans. Reliab. 53 (2004), pp. 349–356]. Finally, we illustrate the proposed goodness-of-fit tests using two real data from reliability literature.     

A Parametric Test of Perfect Ranking in Balanced Ranked Set Sampling

Many techniques based on data which are drawn by Ranked Set Sampling (RSS) scheme assume that the ranking of observations is perfect. Therefore it is essential to develop some methods for testing this assumption. In this article, we propose a parametric location-scale free test for assessing the assumption of perfect ranking. The results of a simulation study in two special cases of normal and exponential distributions indicate that the proposed test performs well in comparison with its leading competitors.     

Testing the Equality and Exchangeability of Bivariate Distributions

We consider three methods (oments, cut-points, and ranks) for testing the hypotheses of equality of two bivariate distribution functions (H _0a ) and exchangeability (H _0b ). To test H _0a , the asymptotic normality of the vector of mixed moments provides a statistic with an asymptotic chi-square distribution. With every observation, method of cut-points associates three 2 × 2 tables to record the proportions of the X, Y, and the combined samples that fall in the four regions around the observation. We measure the total squared deviations of the proportions in the combined sample from X and Y samples. The two methods are compared with the method of ranks based on the Puri and Sen (1971 Puri , M. L. , Sen , P. K. ( 1971 ). Nonparametric Methods in Multivariate Analysis . New York : John Wiley and Sons . [Google Scholar]) multivariate two-sample rank test for location.

To test H _0b we identify two bivariate distributions, one above and the other below the line of symmetry X = Y, to which a test of H _0a is applied. Under H _0b , matrix of mixed moments is symmetric and a quadratic form in differences of (r,s)-th and (s, r)-th mixed moments provides an asymptotic chi-square distribution. A permutation test is devised to apply the method of cut-points to the observations above and below the line of symmetry after they are folded. We also describe an adaption of the Puri-Sen rank test to assess H _0b . To estimate the power of the above methods under different types of alternatives and compare them to existing tests, we report on a Monte Carlo experiment that evaluates the finite-sample performance of these methods under the Plackett's family of bivariate distributions.     

Testing the difference between two independent regression models

ABSTRACT

In some situations, for example, in biology or psychology studies, we wish to determine whether the linear relationship between response variable and predictor variables differs in two populations. The analysis of the covariance (ANCOVA) or, equivalently, the partial F-test approaches are the commonly used methods. In this study, the asymptotic distribution for the difference between two independent regression coefficients was established. The proposed method was used to derive the asymptotic confidence set for the difference between coefficients and hypothesis testing for the equality of the two regression models. Then a simulation study was conducted to compare the proposed method with the partial F method. The performance of the new method was comparable with that of the partial F method.     

An objective look at obtaining the plotting positions for QQ-plots

ABSTRACT

Choosing the plotting positions for the QQ-plot has been a subject of much debate in the statistical and engineering literature. This paper looks at this problem objectively by considering three frameworks: distribution-theoretic; decision-theoretic; game-theoretic. In each framework, we derive the plotting positions and show that there are more than one legitimate solution depending on the practitioner’s objective. This work clarifies the choice of the plotting positions by allowing one to easily find the mathematical equivalent of their view and choose the corresponding solution. This work also discusses approximations to the plotting positions when no closed form is available.     

Geostatistical analysis of disease data: a case study of tuberculosis incidence in Iran

The main objective of this study is to introduce two advanced statistical methods and to consider geographical distribution of tuberculosis incidence in Iran. With the knowledge that environmental and climatic conditions in each region are affective for the incidence and spread of the disease, the study has been taken into consideration. The disease incidences in different counties are realizations of spatial data, therefore we apply the Poisson kriging and ordinary kriging for prediction of tuberculosis incidence rates map in Iran. To identify high risk areas using statistical map of disease, our results show that tuberculosis incidences are not uniformly distributed in whole of the country and estimated risk is high in the eastern parts. Assessing geographical distribution of a disease is essential for health officials to recognize high-risk areas, and improve case management and resource allocation.