Penalized contrast estimation in functional linear models with circular data

Our aim is to estimate the unknown slope function in the functional linear model when the response Y is real and the random function X is a second-order stationary and periodic process. We obtain our estimator by minimizing a standard (and very simple) mean-square contrast on linear finite dimensional spaces spanned by trigonometric bases. Our approach provides a penalization procedure which allows to automatically select the adequate dimension, in a non-asymptotic point of view. In fact, we can show that our penalized estimator reaches the optimal (minimax) rate of convergence in the sense of the prediction error. We complete the theoretical results by a simulation study and a real example that illustrates how the procedure works in practice.     

Understanding preferences for tree attributes: the relative effects of socio-economic and local environmental factors

Urban plant biodiversity is influenced by both the physical environment and attitudes and preferences of urban residents for specific plant types. Urban residents are assumed to be disconnected from their immediate environment, and cultural and societal factors have been emphasized over environmental factors in studies of landscaping choices. However, we postulate that local climatic and environmental factors can also affect preferences for plant attributes. Therefore, spatial and temporal patterns in urban tree biodiversity may be driven not only by the direct effect of environmental variables on plant function, but also by the effect of environmental variables on attitudes toward trees and associated choices about which types of trees to plant. Here, we tested the relative effects of socio-economic and local environmental factors on preferences toward tree attributes in five counties in southern California in and surrounding Los Angeles, based on 1,029 household surveys. We found that local environmental factors have as strong an effect on preferences for tree attributes as socio-economic factors. Specifically, people located in hotter climates (average maximum temperature 25.1 °C) were more likely to value shade trees than those located in cooler regions (23.1 °C). Additionally, people located in desert areas were less likely to consider trees to be important in their city compared with people located in naturally forested areas. Overall, our research demonstrates the inherent connections between local environmental factors and perceptions of nature, even in large modern cities. Accounting for these factors can contribute to the growing interest in understanding patterns of urban biodiversity.     

Combinatorics and Statistical Issues Related to the Kruskal–Wallis Statistic

We explore criteria that data must meet in order for the Kruskal–Wallis test to reject the null hypothesis by computing the number of unique ranked datasets in the balanced case where each of the m alternatives has n observations. We show that the Kruskal–Wallis test tends to be conservative in rejecting the null hypothesis, and we offer a correction that improves its performance. We then compute the number of possible datasets producing unique rank-sums. The most commonly occurring data lead to an uncommonly small set of possible rank-sums. We extend prior findings about row- and column-ordered data structures.     

Supplementing a survey with respondent Twitter data to measure e-cigarette information exposure

ABSTRACT

Social media data are increasingly used by researchers to gain insights on individuals’ behaviors and opinions. Platforms like Twitter provide access to individuals’ postings, networks of friends and followers, and the content to which they are exposed. This article presents the methods and results of an exploratory study to supplement survey data with respondents’ Twitter postings, networks of Twitter friends and followers, and information to which they were exposed about e-cigarettes. Twitter use is important to consider in e-cigarette research and other topics influenced by online information sharing and exposure. Further, Twitter metadata provide direct measures of user’s friends and followers as opposed to survey self-reports. We find that Twitter metadata provide similar information to survey questions on Twitter network size without inducing recall error or other measurement issues. Using sentiment coding and machine learning methods, we find Twitter can elucidate on topics difficult to measure via surveys such as online expressed opinions and network composition. We present and discuss models predicting whether respondents’ tweet positively about e-cigarettes using survey and Twitter data, finding the combined data to provide broader measures than either source alone.     

What's wrong is right: A response to the state of the discipline

In the June issue ofSociological Forum, several authors addressed the question, What's Wrong with Sociology. Answers included increased fragmentation of the discipline, and the lack of an identifiable cumulative core of sociological knowledge. This paper examines many of the claims made by the contributors to the June 1994Sociological Forum, reframes their arguments, and by placing debates regarding the problems in sociology in a broader perspective, identifies many of the recent advances made by the discipline. Focusing on such notable contributions to the field as feminist and postmodern scholarship, we locate the positive side of multiple perspective research.Feminist Scholars in Sociology is a collective of researchers and teachers at the University of Colorado interested in exploring and sharing feminist theory and methodology.     

Do females necessarily have the same occupational status scores as males? A conceptual and empirical examination of the Duncan Socioeconomic Status Index and Nam-Powers Occupational Status Scores

Social Science researchers have advanced important yet somewhat contradictory conclusions regarding the different economic and occupational reward structures faced by men and women. Income and wage differences between men and women have been shown to be sizable and persistent throughout the occupational hierarchy. Conversely, gender differences in occupational status, commonly scaled by the Duncan Socioeconomic Index, have been shown to be small or nonexistent in most studies. In an attempt to investigate this incongruity, the present study undertakes a comparison of the Duncan SEI and the Nam-Powers Occupational Status Scores in an empirical study of the occupational position of white men and women in 65 large standard metropolitan statistical areas (SMSAs) in 1970. While the findings of earlier studies showing no gender differences in occupational status are for the most part replicated using the Duncan SEI, use of the Nam-Powers scores prompts a much different conclusion. Large status differences between men and women are indicated using this latter scale, differences which are very much in line with income differences commonly cited. We suggest that the Nam-Powers metric should be used instead of the Duncan SEI in studies of occupational status of women and men.