USE OF EXPERT RATINGS AS SAMPLING STRATA FOR A MORE COST-EFFECTIVE PROBABILITY SAMPLE OF A RARE POPULATION

We consider situations in which externally observable characteristics allow experts to quickly categorize individual households as likely or unlikely to contain a member of a rare target population. This classification can form the basis of disproportionate stratified sampling such that households classified as "unlikely" are sampled at a lower rate than those classified as "likely," thereby reducing screening costs. Design weights account for this approach and allow unbiased estimates for the target population.We demonstrate that with sensitivity and specificity of expert classification at least 70%, and ideally at least 80%, our approach can economically increase effective sample size for a rare population. We develop heuristics for implementing this approach and demonstrate that sensitivity drives design effects and screening costs whereas specificity only drives the latter. We demonstrate that the potential gains from this approach increase as the target population becomes rarer. We further show that for most applications, unlikely strata should be sampled at 1/6 to ? the rate of likely strata.This approach was applied to a survey of Cambodian immigrants in which the 82% of households rated "unlikely" were sampled at ? the rate as "likely" households, reducing screening from 9.4 to 4.0 approaches per complete. Sensitivity and specificity were 86% and 91% respectively. Weighted estimation had a design effect of 1.26 so screening costs per effective sample size were reduced 47%. We also note that in this instance, expert classification appeared to be uncorrelated with survey outcomes of interest among eligibles.     

Inviting the Breach: Confronting Homophobia in the Name of Social Justice

In 2008 California was divided over Proposition 8, a measure designed to prohibit same-sex marriage. In this article, we focus on a university classroom setting to explore how discussions about Proposition 8 and homophobia led to what Turner (1986) termed a social drama. Drawing on student personal narratives as they moved through the stages of social drama, we provide a poignant example of the conflict that may erupt when homophobia and heteronormativity are part of the curriculum. After documenting the social drama, we offer pedagogical strategies and note the strategic ways Christian, hegemonic discourse is utilized during discussions about homophobia.     

Recognizing Emotions in a Foreign Language

Expressions of basic emotions (joy, sadness, anger, fear, disgust) can be recognized pan-culturally from the face and it is assumed that these emotions can be recognized from a speaker’s voice, regardless of an individual’s culture or linguistic ability. Here, we compared how monolingual speakers of Argentine Spanish recognize basic emotions from pseudo-utterances (“nonsense speech”) produced in their native language and in three foreign languages (English, German, Arabic). Results indicated that vocal expressions of basic emotions could be decoded in each language condition at accuracy levels exceeding chance, although Spanish listeners performed significantly better overall in their native language (“in-group advantage”). Our findings argue that the ability to understand vocally-expressed emotions in speech is partly independent of linguistic ability and involves universal principles, although this ability is also shaped by linguistic and cultural variables.

Social Confidence in Unions: A U.S.‐Canada Comparison

Cet article examine l’évolution des niveaux de confiance sociale envers les organisations syndicales au Canada et aux États‐Unis entre 1982 et 2006 en s'appuyant sur les données de la World Value Survey (WVS). Partant du constat que ces taux de confiance sont relativement similaires au sein de ces deux pays, nous appliquons un modèle de régression logistique sur les deux vagues de données les plus récentes du WVS (soit celle de 2000 et 2006) afin de mieux comprendre la propension des individus à faire confiance aux syndicats dans chaque contexte national en fonction de certaines de leurs caractéristiques sociales et politiques. Les résultats montrent des similitudes entre les deux pays (par exemple, les citoyens les plus progressistes et les plus jeunes ont généralement une plus grande confiance envers les syndicats), mais également des distinctions importantes (à titre d'exemple, seul au Canada les individus répondant à un profil de “classe ouvrière” manifestent une plus grande confiance envers les syndicats). This article examines changes in levels of social confidence in unions in Canada and the United States between 1982 and 2006 based on an analysis of the World Value Survey (WVS) data set. It considers why confidence rates are similar in the two countries, applying a logistic regression model to the two most recent WVS waves (i.e., 2000 and 2006) so as to bring out the effects of political and social differences on the propensity of individuals to trust unions in each national context. The results show similarities between the two countries (e.g., more progressive and younger citizens generally have greater confidence in unions), but also important distinctions (e.g., only in Canada do individuals with a working class profile appear to have greater confidence in unions).     

Assessing Type I error and power of multistate Markov models for panel data—A simulation study

Ordinal outcomes collected at multiple follow-up visits are common in clinical trials. Sometimes, one visit is chosen for the primary analysis and the scale is dichotomized amounting to loss of information. Multistate Markov models describe how a process moves between states over time. Here, simulation studies are performed to investigate the Type I error and power characteristics of multistate Markov models for panel data with limited non-adjacent state transitions. The results suggest that the multistate Markov models preserve the Type I error and adequate power is achieved with modest sample sizes for panel data with limited non-adjacent state transitions.