Oppositional Girlhoods and the Challenge of Relational Politics

Over the last five years, scholars from a wide variety of disciplines have problematized the discourse of “adolescent female exceptionalism” (Switzer in Fem Theory 14(3):345–360, 2013, p. 4) popularized by the NIKE Foundation’s Girl Effect. Arriving at similar conclusions, scholars point to the artificial neocolonial divisions between ‘the West’ and ‘the rest’ of the world animated by an ‘invest in girls’ logic. This paper endeavors to move beyond the “oppositional girlhoods” (Bent in Sociol Stud Child Youth 16(1):3–20, 2013a, p. 7) bind of girl effects discourse to propose that differentially positioned and experienced girlhoods might be better understood as transnational, relational cultural formations. Drawing from our empirical research with girls in North America and Sub-Saharan Africa, we consider the implications of girls’ increasing global visibility as the ‘saviors of humanity’ from different geopolitical contexts. We then go further to suggest the oppositional girlhoods frame assumes reductive, apolitical, and ahistorical claims of divergence between girlhoods in the Global North and Global South “with highly unequal effects” (Gonick et al. in Girlhood Stud 2(3):1–9, 2009, p. 3). By countering the normative construction of global girlhoods as mutually exclusive forms of personhood and historical experience, our project authorizes a new understanding of girlhoods as mutually constituted and relationally contingent. It is from within this relational framework that we propose new directions for thinking about girlhoods transnationally.     

A Comparison of Some Methods for the Selection of a Common Eigenvector Model for the Covariance Matrices of Two Groups

Two new nonparametric common principal component model selection procedures based on bootstrap distributions of the vector correlations of all combinations of the eigenvectors from two groups are proposed. The performance of these methods is compared in a simulation study to the two parametric methods previously suggested by Flury in 1988, as well as modified versions of two nonparametric methods proposed by Klingenberg in 1996 and then by Klingenberg and McIntyre in 1998. The proposed bootstrap vector correlation distribution (BVD) method is shown to outperform all of the existing methods in most of the simulated situations considered.     

Testing Hypotheses in Nonparametric Models of Production

Data envelopment analysis (DEA) and free disposal hull (FDH) estimators are widely used to estimate efficiency of production. Practitioners use DEA estimators far more frequently than FDH estimators, implicitly assuming that production sets are convex. Moreover, use of the constant returns to scale (CRS) version of the DEA estimator requires an assumption of CRS. Although bootstrap methods have been developed for making inference about the efficiencies of individual units, until now no methods exist for making consistent inference about differences in mean efficiency across groups of producers or for testing hypotheses about model structure such as returns to scale or convexity of the production set. We use central limit theorem results from our previous work to develop additional theoretical results permitting consistent tests of model structure and provide Monte Carlo evidence on the performance of the tests in terms of size and power. In addition, the variable returns to scale version of the DEA estimator is proved to attain the faster convergence rate of the CRS-DEA estimator under CRS. Using a sample of U.S. commercial banks, we test and reject convexity of the production set, calling into question results from numerous banking studies that have imposed convexity assumptions. Supplementary materials for this article are available online.     

Power analysis for clustered non-continuous responses in multicenter trials

Power analysis for multi-center randomized control trials is quite difficult to perform for non-continuous responses when site differences are modeled by random effects using the generalized linear mixed-effects model (GLMM). First, it is not possible to construct power functions analytically, because of the extreme complexity of the sampling distribution of parameter estimates. Second, Monte Carlo (MC) simulation, a popular option for estimating power for complex models, does not work within the current context because of a lack of methods and software packages that would provide reliable estimates for fitting such GLMMs. For example, even statistical packages from software giants like SAS do not provide reliable estimates at the time of writing. Another major limitation of MC simulation is the lengthy running time, especially for complex models such as GLMM, especially when estimating power for multiple scenarios of interest. We present a new approach to address such limitations. The proposed approach defines a marginal model to approximate the GLMM and estimates power without relying on MC simulation. The approach is illustrated with both real and simulated data, with the simulation study demonstrating good performance of the method.     

Investigating impacts of complex sampling on latent growth curve modelling

We investigate the impacts of complex sampling on point and standard error estimates in latent growth curve modelling of survey data. Methodological issues are illustrated with empirical evidence from the analysis of longitudinal data on life satisfaction trajectories using data from the British Household Panel Survey, a national representative survey in Great Britain. A multi-process second-order latent growth curve model with conditional linear growth is used to study variation in the two perceived life satisfaction latent factors considered. The benefits of accounting for the complex survey design are considered, including obtaining unbiased both point and standard error estimates, and therefore correctly specified confidence intervals and statistical tests. We conclude that, even for the rather elaborated longitudinal data models that were considered, estimation procedures are affected by variance-inflating impacts of complex sampling.     

Sampling Telephone Numbers and Adults, Interview Length, and Weighting in The California Health Interview Survey Cell Phone Pilot Study

This article describes several features included in a CaliforniaHealth Interview Survey cell phone pilot study that differ fromearlier cell phone surveys conducted in the United States. Onedifference is that the study used a screening design and onlyadults living in cell-only households were interviewed. Mostof the previous studies used dual frame designs. Another differencewas the development and implementation of a within-householdadult sampling procedure to cover adults when cell phones wereshared in the household. The study was also intended to determineif conducting a cell phone interview of the same scope and lengthas a regular telephone interview was feasible. Most previoussurveys were focused on cell phone topics and were shorter thanthe comparable landline surveys. We then explore some interestingproblems that arise in weighting a cell phone survey using ascreening design. We conclude with a discussion of planninga new cell phone survey in 2007 that incorporates findings fromthis study.     

Characteristics of children in residential treatment in New York State

This study addresses three questions about the population of children and families served in the highest level of care in the child welfare system in New York State residential treatment centers (RTCs): (1) How prevalent are emotional and behavioral problems in the youth entering RTCs? (2) Has the proportion of youth with such problems increased compared to 10 years ago? (3) Are there identifiable subgroups of youth entering RTCs? One-fourth of RTC admissions in fiscal year 2001 were randomly selected from a representative sample of 16 RTCs. The study completed a standardized data collection instrument based on a review of agency records, and included information that was known at the time each child was admitted. The results show significant increases compared to t10 years earlier in the proportion of youth with mental health problems and juvenile justice backgrounds. The findings suggest that youth who traditionally have been served by other systems of care are now being served in the child welfare system. The increased treatment needs of these youth and the heterogeneity of the RTC population have important implications for policies, programs, and practice.     

Protective and risk influences of drug use among a multiethnic sample of adolescent boys

A measurement model was analyzed to demonstrate a differential distribution and cumulative exposure to psychosocial risk and protective influences of adolescent drug use among ethnically-diverse adolescent samples. The sample included U.S.-born (US) Latino (N = 837), foreign-born (FB) Latino (N = 447), White (N = 632), and African American (N = 618) adolescent boys. Psychological Distress, Peer Drug Use, and Adolescent Drug Use were significantly positively correlated with Peer Drug Use and Adolescent Drug Use. In contrast, Family, School, law abidance, and guilt were significantly negatively correlated with Peer Drug Use and Adolescent Drug Use. Multiple group analyses indicated significant similarities and differences among US and FB Latinos, and Whites. Implications for early prevention, multi-level interventions, and suggestions for future research are discussed.     

Injunctive Norms and Problem Gambling among College Students

Two studies examined the relationships among injunctive norms and college student gambling. In study 1 we evaluated the accuracy of perceptions of other students’ approval of gambling and the relationship between perceived approval and gambling behavior. In study 2 we evaluated gambling behavior as a function of perceptions of approval of other students, friends, and family. In study 1, which included 2524 college students, perceptions of other students’ approval of gambling were found to be overestimated and were negatively associated with gambling behavior. The results of study 2, which included 565 college students, replicated the findings of study 1 and revealed positive associations between gambling behavior and perceived approval of friends and family. Results highlight the complexity of injunctive norms and the importance of considering the reference group (e.g., peers, friends, family members) in their evaluation. Results also encourage caution in considering the incorporation of injunctive norms in prevention and intervention approaches.     

Gambling and Alcohol Use: Trends in the State of New Mexico from 1996–1998

Alcohol consumption and its relationship to gambling was examined in a statewide New Mexico survey in 1996 and 1998. Data regarding both drinking habits and gambling behavior were obtained from a stratified random sample of the adult population (N = 2674) across the entire State of New Mexico via phone survey. These surveys were carried out shortly after a period when New Mexico experienced an initial surge in the legalized gaming industry. Fifty-seven percent of survey respondents reported drinking in the past month, while 43.1% reported no drinking in the past 30 days. Results show that while the number of days in the past 30 that a person drinks is significantly correlated with some types of gambling behavior (e.g., in 1998, drinking more days was associated with more card gambling and sports gambling), it is the amount of alcohol consumed per occasion that is associated with more gambling behavior. For example, in both 1996 and 1998, drinking more per occasion was associated with more sports betting, dice gambling, number/lottery gambling, gambling using machines, and paper game gambling (e.g., pull tabs, punchboard). These results suggest that problem gambling behavior is not affected as much by the number of occasions on which one consumes alcohol, as by the amount of alcohol consumed per occasion.