Predicting distances using a linear model: the case of varietal distinctness

Differences between plant varieties are based on phenotypic observations, which are both space and time consuming. Moreover, the phenotypic data result from the combined effects of genotype and environment. On the contrary, molecular data are easier to obtain and give a direct access to the genotype. In order to save experimental trials and to concentrate efforts on the relevant comparisons between varieties, the relationship between phenotypic and genetic distances is studied. It appears that the classical genetic distances based on molecular data are not appropriate for predicting phenotypic distances. In the linear model framework, we define a new pseudo genetic distance, which is a prediction of the phenotypic one. The distribution of this distance given the pseudo genetic distance is established. Statistical properties of the predicted distance are derived when the parameters of the model are either given or estimated. We finally apply these results to distinguishing between 144 maize lines. This case study is very satisfactory because the use of anonymous molecular markers (RFLP) leads to saving 29% of the trials with an acceptable error risk. These results need to be confirmed on other varieties and species and would certainly be improved by using genes coding for phenotypic traits.     

Estimation of long-run inefficiency levels: a dynamic frontier approach

Cornwell, Schmidt, and Sickles (1990) and Kumbhakar (1990), among others, developed stochasticfrontier production models which allow firm specific inefficiency levels to change over time. These studies assumed arbitrary restrictions on the short-run dynamics of efficiency levels which have little theoretical justification. Further, the models are inappropriate for estimation of long-run efficiencies. We consider estimation of an alternative frontier model in which firmspecific technical inefficiency levels are autoregressive. This model is particularly useful to examine a potential dynamic link between technical innovations and production inefficiency levels. We apply our methodology to a panel of US airlines.     

Shrinkage confidence intervals for the normal mean: Using a guess for greater efficiency

If the unknown mean of a univariate population is sufficiently close to the value of an initial guess then an appropriate shrinkage estimator has smaller average squared error than the sample mean. This principle has been known for some time, but it does not appear to have found extension to problems of interval estimation. The author presents valid two‐sided 95% and 99% “shrinkage” confidence intervals for the mean of a normal distribution. These intervals are narrower than the usual interval based on the Student distribution when the population mean lies in such an “effective interval.” A reduction of 20% in the mean width of the interval is possible when the population mean is sufficiently close to the value of the guess. The author also describes a modification to existing shrinkage point estimators of the general univariate mean that enables the effective interval to be enlarged.     

A mixture model for random graphs

The Erdös–Rényi model of a network is simple and possesses many explicit expressions for average and asymptotic properties, but it does not fit well to real-world networks. The vertices of those networks are often structured in unknown classes (functionally related proteins or social communities) with different connectivity properties. The stochastic block structures model was proposed for this purpose in the context of social sciences, using a Bayesian approach. We consider the same model in a frequentest statistical framework. We give the degree distribution and the clustering coefficient associated with this model, a variational method to estimate its parameters and a model selection criterion to select the number of classes. This estimation procedure allows us to deal with large networks containing thousands of vertices. The method is used to uncover the modular structure of a network of enzymatic reactions.     

Beyond New Zealand's Dual Health Reforms

The New Zealand health system was substantially reformed in 1993 with the introduction of a purchaser–provider split, competitive contracting and managerialism. The new system failed to deliver the desired gains and, in 1996, the reforms were reformed. While there has been widespread study of the 1993 reforms, there has been little discussion to date of the 1996 changes and the emerging directions for New Zealand health policy and service delivery, which remain unclear. This paper discusses the New Zealand health reforms of the 1990s. It briefly outlines the 1993 reforms and their results. Next, it details the 1996 reforms. Third, it discusses developments since 1996, some of which have emerged out of the 1993 reforms, but which have gathered momentum only since the 1996 changes were announced. In the conclusion, the paper lists some of the directions in which the New Zealand health sector appears to be heading, noting that there is a need for coordination of the sector, and for permanence.     

Data availability in accounting research: Some evidence

The data availability policy of the American Accounting Association is examined to address two research questions: (1) Are data dependent results in The Accounting Review readily available for further inquiry and dissemination of accounting knowledge? (2) What are the potential factors that may account for the availability or the lack of data? Several potential factors including job rank, number of revisions before acceptance, source of data, and funding source are suggested to account for the lack of data availability. The results indicate that, in general, authors are not willing to make their data available to others. We conclude by suggesting some options that may ameliorate the situation.     

The Role of Social Goals in Bullies' and Victims' Social Information Processing in Response to Ambiguous and Overtly Hostile Provocation

Understanding what social goals are associated with bullying and victimization behaviours, even after allowing for biases in interpretation of and affective responses to social events, is critical for understanding the socio‐behavioural profile of bullies and victims. In the present study, 181 nine‐ to ten‐year‐olds' affective responses, attribution of intent, and social goals were assessed in the context of a series of ambiguous and overtly hostile provocation vignettes. Results showed that even after allowing for other social information processing biases, social goals were meaningfully associated with bullying and victimization scores. Bullying was inversely associated with relationship‐building goals, and positively associated with goals to be assertive over the provocateur when provocation was overtly hostile. Being victimized was associated with having submissive goals even when provocation was ambiguous and after accounting for attribution of hostile intent. Findings are discussed in light of theoretical and practical implications.     

Sex differences in the vocabulary of college students

The present study replicated Jastrow's 1891 experiment concerning differences between male and female vocabulary. Participants were 20 male and 20 female Caucasian middle‐class college students. They recorded up to 100 nouns in a 15‐minute period. Results indicate that women have increased their use of unusual words compared to women in 1891. Males used more scientific words and more body part words than females. In contrast to the previous study, there are no significant differences between the sexes in use of animal, nature, and food words. Females used more clothing words than males in this study, as in the previous study, and produced more different words than males. Vocabulary changes appear to reflect changes in the social structure of the society.     

An Evaluation of Behavioral Health Compliance and Microbial Risk Factors on Student Populations Within a High-Density Campus

Abstract

Objective: The aim of this Canadian study was to assess student behavioral response to disease transmission risk, while identifying high microbial deposition/transmission sites. Participants: A student survey was conducted during October 2009. Methods: The methods included a survey of students to assess use of health services, vaccination compliance, and hygiene along with a microbial analysis of potential transmission sites targeting specific residence buildings on campus. Results: Results indicated that most students maintained that they were worried about H1N1 and reported making changes in hygienic behavior, with the majority not planning to be vaccinated. The microbial analysis indicated contamination of fomites in co-ed residences to be higher than either male or female student residences. Conclusions: A consideration of physical space along with behavioral factors is required in order to properly assess risk pathways in the establishment of an evidence-based infection control plan for universities and their contiguous communities.