Probabilistic Models for Bacterial Taxonomy

We give a survey of different partitioning methods that have been applied to bacterial taxonomy. We introduce a theoretical framework, which makes it possible to treat the various models in a unified way. The key concepts of our approach are prediction and storing of microbiological information in a Bayesian forecasting setting. We show that there is a close connection between classification and probabilistic identification and that, in fact, our approach ties these two concepts together in a coherent way.     

The Black Enterprise Magazine Ranking of Colleges for African Americans: A Structural Analysis

This paper assesses the Black Enterprise Magazine (BE) ranking of the “top 50 colleges for African Americans,” which it publishes biennially. Its principal objective is to evaluate the statistical consistency in the ranking over the distribution of institutions that compose it. The paper attempts to address two-related questions. Does the BE report provide an unbiased and consistent assessment of the educational value associated with the institutions included in their listing? Is the ranking method internally consistent? Two experiments were used to evaluate the consistency of the BE ranking. First, structural difference in the model used to rank the institutions in the upper and lower half of the distribution is tested. Second, structural difference in the model used to rank HBCU and non-HBCU institutions included in the BE listed ranking is tested. In both cases the null hypothesis of the same structure is rejected.     

Bayesian and Frequentist Inference for Ecological Inference: The R×C Case

In this paper we propose Bayesian and frequentist approaches to ecological inference, based on R × C contingency tables, including a covariate. The proposed Bayesian model extends the binomial-beta hierarchical model developed by K ing , R osen and T anner (1999) from the 2×2 case to the R × C case. As in the 2×2 case, the inferential procedure employs Markov chain Monte Carlo (MCMC) methods. As such, the resulting MCMC analysis is rich but computationally intensive. The frequentist approach, based on first moments rather than on the entire likelihood, provides quick inference via nonlinear least-squares, while retaining good frequentist properties. The two approaches are illustrated with simulated data, as well as with real data on voting patterns in Weimar Germany. In the final section of the paper we provide an overview of a range of alternative inferential approaches which trade-off computational intensity for statistical efficiency.     

Modeling Clustered Ordered Categorical Data: A Survey

This article surveys various strategies for modeling ordered categorical (ordinal) response variables when the data have some type of clustering, extending a similar survey for binary data by Pendergast, Gange, Newton, Lindstrom, Palta & Fisher (1996). An important special case is when repeated measurement occurs at various occasions for each subject, such as in longitudinal studies. A much greater variety of models and fitting methods are available than when a similar survey for repeated ordinal response data was prepared a decade ago (Agresti, 1989). The primary emphasis of the review is on two classes of models, marginal models for which effects are averaged over all clusters at particular levels of predictors, and cluster-specific models for which effects apply at the cluster level. We present the two types of models in the ordinal context, review the literature for each, and discuss connections between them. Then, we summarize some alternative modeling approaches and ways of estimating parameters, including a Bayesian approach. We also discuss applications and areas likely to be popular for future research, such as ways of handling missing data and ways of modeling agreement and evaluating the accuracy of diagnostic tests. Finally, we review the current availability of software for using the methods discussed in this article.     

Estimation bias in choice models with last choice feedback

The study compares two estimation methods for choice models with last choice feedback, using simulated and real data. The first method ignores the impact of unobserved heterogeneity on observed choices via presample choices, while the second method approximates this impact by a stochastic relationship. In panels with less than 10 choices per panelist, the first method overstates the impact of last choice on current choice and understates the impact of intrinsic preferences (i.e., brand intercepts). The second method performs significantly better than the first method. Under both methods, an increase in the number of heterogeneous coefficients in the model tends to increase the bias in the estimates. The largest bias occurs when lagged choice coefficients are heterogeneous.     

特区大学生就业意向调查统计分析

1999年高校扩招以来,高校毕业生的数量迅速增加,大学毕业生的就业问题成为社会关注的焦点,在这个阶段,特区大学毕业生同样受到了就业压力的冲击,及时了解特区大学生的就业意向及就业心理,对于特区学校制定正确的就业指导方向具有重要的意义,是深化以就业为导向的高等教育改革,培养合格就业人才的重要依据。     

THE "VEREENIGING VOOR DE STATISTIEK", 1857–1892

This paper deals with the history of the nineteenth century Dutch statistical society: "Vereeniging voor de Statistiek", founded in 1857. In the second half of the nineteenth century the society flourished and had a considerable amount of members. It played a very active role for the establishment of a central official statistical bureau: "Centraal Bureau voor de Statistiek". These activities ended with success in 1892. Then the society changed its name and did no longer engage itself with statistics. Members of the statistical society thought of statistics as facts about society, mostly numerical, but not always. They hoped to discover the laws which ruled society, by means of statistics. In that way the social sciences would improve.     

A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies

This paper uses Bayesian stochastic frontier methods to measure the productivity gap between Poland and Western countries that existed before the beginning of the main Polish economic reform. Using data for 20 Western economies, Poland and Yugoslavia (1980–1990) we estimate a translog stochastic frontier and make inference about individual efficiencies. Following the methodology proposed in our earlier work, we also decompose output growth into technical, efficiency and input changes and examine patterns of growth in the period under consideration. This revised version was published online in July 2006 with corrections to the Cover Date.     

Reciprocity,Multiplexity, and Exchange: Measures

We introduce measures and statistical tests for multiplexity and exchange that are modeled on similar ideas developed for reciprocity quite early in the history of social network research. As properties of a multi-relation network, multiplexity, and exchange have almost as ancient a history as reciprocity, but have not been as intensively investigated from a methodological perspective. Multiplexity refers to the extent to which two ties, for example, advice and friendship, coincide over population; that is, do respondents name the same people as friends as the persons they nominate as individuals from who they seek advice. Exchange refers to the extent to which a tie of one type directed from person i to person j is returned by a tie of another type from j to i. We conceive of the current paper as the first part of a two-part paper, wherein the second part explores specific theoretical models for multiplexity and exchange.     

Statistical Thinking in Computer-Based Learning Environments

The theme of technology is particularly important for statistics education because of the role of technology in changing views of statistical knowledge, pedagogy and learning. The interactive multimedia technology of today allows for the creation of powerful learning environments where the focus is on the process that produced the data and its associated variation and the statistical thinking required to solve the problem. However, despite this optimistic view, students' self‐regulation and intrinsic motivation seem to be key concepts for learning in complex interactive computer‐based learning environments. We conclude with observations of teachers and students working with applets. More of these evaluations should be published and/or made available to the statistical community so that both positive and negative teaching experiences can be shared.