A varying coefficient approach to estimating hedonic housing price functions and their quantiles

The varying coefficient (VC) model introduced by Hastie and Tibshirani [26 T. Hastie and R. Tibshirani, Varying-coefficient models, J. R. Statist. Soc. (Ser. B) 55 (1993), pp. 757–796.[Web of Science ®] , [Google Scholar]] is arguably one of the most remarkable recent developments in nonparametric regression theory. The VC model is an extension of the ordinary regression model where the coefficients are allowed to vary as smooth functions of an effect modifier possibly different from the regressors. The VC model reduces the modelling bias with its unique structure while also avoiding the ‘curse of dimensionality’ problem. While the VC model has been applied widely in a variety of disciplines, its application in economics has been minimal. The central goal of this paper is to apply VC modelling to the estimation of a hedonic house price function using data from Hong Kong, one of the world's most buoyant real estate markets. We demonstrate the advantages of the VC approach over traditional parametric and semi-parametric regressions in the face of a large number of regressors. We further combine VC modelling with quantile regression to examine the heterogeneity of the marginal effects of attributes across the distribution of housing prices.     

Smoothing the difference-based estimates of variance using variational mode decomposition

We propose a variational mode decomposition approach to estimate the variance function in a nonparametric heteroscedastic fixed design regression model. A data-driven estimator is constructed by applying variational mode decomposition technique to the difference-based initial estimates. The numerical results show that the proposed estimator performs better than the existing variance estimation procedures in the mean square sense.     

Optimal and lead-in adaptive allocation for binary outcomes: A comparison of Bayesian methods

We compare posterior and predictive estimators and probabilities in response-adaptive randomization designs for two- and three-group clinical trials with binary outcomes. Adaptation based upon posterior estimates are discussed, as are two predictive probability algorithms: one using the traditional definition, the other using a skeptical distribution. Optimal and natural lead-in designs are covered. Simulation studies show that efficacy comparisons lead to more adaptation than center comparisons, though at some power loss, skeptically predictive efficacy comparisons and natural lead-in approaches lead to less adaptation but offer reduced allocation variability. Though nuanced, these results help clarify the power-adaptation trade-off in adaptive randomization.     

Public Sociology on Twitter: a Space for Public Pedagogy?

Research has examined various elements of Twitter; however, no scholarship has explored how sociologists currently use the platform. This empirically driven paper explores how individuals that self-identify as sociologists on Twitter use the popular micro-blogging social media site. A total of 152,977 tweets from Twitter profiles of 130 sociologists were collected and examined using qualitative media analysis. The potential use of Twitter allows the sociologist to become both the generator and interlocutor of dialogue with publics. We frame our data analysis and discussion around the core theme of expertise - namely, the role that expertise plays in the use of Twitter by sociologists. Our findings indicate that when sociologists used Twitter as sociologists (i.e., drawing upon their stated research expertise) little direct engagement with publics occurred. Thus, while sociologists appear to be using Twitter as a space for public sociology, the use of this interactive platform is mostly limited to the generation of content, a finding consistent with Burawoy’s traditional form of public sociology. Suggestions for future research are noted.     

Standard Bearers: Qualitative Sociologists’ Experiences with IRB Regulation

In response to the system for regulating research with human subjects, researchers have raised two apparently contradictory concerns: that IRBs are excessively inconsistent (often raised by biomedical researchers), and that they are excessively standardizing (often raised by qualitative interview researchers). Why does standardization appear as the dominant theme in qualitative researchers’ experiences with their IRBs? And how do qualitative researchers experience standardization in their IRB encounters? We focus on IRBs role as regulatory bureaucracies, which typically rely heavily on standardized communication and decisions to process information and make large numbers of decisions in a timely manner. We explore the role of standardization in IRB regulation of qualitative research in an analysis of semi-structured interviews with 26 qualitative sociologists from six research universities and three liberal arts colleges in the Northeastern United States. In a regulatory regime oriented toward the norms of experimental research, these frictions resulted partly from a lack of appropriate standardized language and decision-templates, but also from the inherent difficulties of applying standardized decisions to work that is unpredictable, unique, and difficult to routinize.     

Cognitive Sociology in France

While cognitive sociology is a relatively new area in U.S. sociology, the subfield has a lengthy history in French sociology. Developing a typology based upon the existing literature, we identify three branches of cognitive sociology in France. The first was initiated by Raymond Boudon, one of the scholars most responsible for popularizing the area, who envisioned cognitive sociology as helping delineate the role of beliefs in rational action. Second, another group of researchers seeks to found sociology upon a naturalistic basis, thus drawing upon the disciplines constitutive of cognitive science (e.g., psychology, cognitive neuroscience, and cognitive anthropology). Finally, the third approach to cognitive sociology in France takes inspiration from linguistics as a foundation for sociological investigations. We conclude the paper by discussing the relationship between these three sub-fields and by examining the relationship between French and American cognitive sociologies in order to identify fruitful directions for future research.     

Networking in France. Is there a French School of Social Network Analysis?

Social Network Analysis (SNA) is a sociology based on interaction that visualizes and models relations between actors. Whereas interaction is approached by classical scholars, we had to wait until the 1970s and the birth of computer science to see social networks analysis develop. This article investigates the influence of SNA in France from the 1980s and wonder if there is a French school of SNA? To do so, we first resume social networks history and highlight its contribution to sociology. Second, we analyze the trajectory and profile of five “disciplinary entrepreneurs,” whose role in the field is important as they master three necessary languages for SNA: English, Mathematics and Computer Science. Third, in order to put back those individuals in their social structures, we cross SNA with the different French sociological tradition(s) (according to topics and methods). Last, we wonder if the institutionalization process succeeded in the creation of institutions from which a French SNA would be able to expand?     

“You Just Don't Understand Me!” Determinants of Second Generation Asian and Latino Youth Self‐Esteem

To understand the integration of second‐generation Asians and Latinos, we study the association between acculturation and self‐esteem, an aspect of psychological wellbeing and belongingness. Using data from the Children of Immigrants Longitudinal Study (CILS), we find that Asians have lower self‐esteem than Latinos. Females, youth who are from lower socioeconomic status families, have been in the US for less than five years, have lower grade point averages, experience discrimination, or experience more family conflict, are at risk for lower self‐esteem. For Asians, identifying as American is associated with higher self‐esteem than identifying by nationality or having a hyphenated identity, but it does not provide a similar benefit to Latinos. Both groups benefit from being fluently bilingual, whereas English‐language dominance is protective only for Asian youths’ self‐esteem. Our analysis nuances the role that acculturation factors play in adolescent self‐esteem, signalling that future research should consider interactions between acculturation and race/ethnicity.     

Family Formation and Close Social Ties Within Religious Congregations

The study of family and religion has yet to elaborate on the social ties that connect these two important and changing institutions. Specifically, how does family formation (i.e., marriage and childrearing) impact social ties to religious communities? Using longitudinal data from the Portraits of American Life Study (2006–2012) and fixed effects regression models that control for time‐stable heterogeneity (N = 1,314), this study tests the effects of marriage and childrearing on changes in close congregational social ties. Fixed effects estimates suggest that marriage actually decreases close social ties to religious congregations, whereas rearing children within marital unions increases them. Thus, it is children, not marriage per se, that actually integrates married couples into religious communities. These contrasting effects tend to be the strongest among young adults, but they weaken with age as well as marital duration.