Shyness,Preference for Solitude,and Adolescent Internalizing: The Roles of Maternal,Paternal, and Best‐Friend Support

The researchers examined differential outcomes related to two distinct motivations for withdrawal (preference for solitude and shyness) as well as the possibility that support from important others (mothers, fathers, and best friends) attenuate any such links. Adolescents (159 males, 171 females) reported on their motivations to withdraw, internalizing symptoms, and relationship quality in eighth grade, as well as their anxiety and depression in ninth grade. Using structural equation modeling, the authors found that maternal support weakened the association between shyness and internalizing problems; friend support weakened the association between preference for solitude and depression; and friend support strengthened the association between shyness and depression. Results suggest that shy adolescents may not derive the same benefits from supportive friendships as their typical peers.     

Exploring experiences of heterosexism and coping strategies among lesbian,gay, bisexual,and transgender persons in Swaziland

Social, cultural, and institutional processes which see heterosexuality as natural and universal discriminate against individuals who differ from this norm. This article draws on interviews with lesbian, gay, bisexual, and transgender (LGBT) people in Swaziland to provide an enhanced understanding of the ways in which heterosexism operates in practice and impacts the sexual rights of LGBT communities in Swaziland, where same-sex practices are criminalised. These narratives show the importance of solidarity and activism in coping strategies to challenge social exclusion, improve lives, and advocate for social changes. These strategies include reframing, navigating interpersonal relationships, and advocacy. We consider key lessons that emerge from our research for policy, programmes, and activism in Swaziland, as well as other low- and middle-income contexts.     

“Everything That We Can Do”: A Content Analysis of the Protective Strategies Used by GLBTQ Parents

Despite increased access to parenting rights through legal marriage and adoption, U.S. gay, lesbian, bisexual, transgender, and queer (GLBTQ) parents continue to experience varying levels of support for their families. This study explored protective strategies, or actions taken to meet one's safety needs when vulnerable, that GLBTQ parents pursue. This study included 454 GLBTQ parents from a national survey. Participants' open-ended responses about protective strategies were extracted from the survey and analyzed using content analysis. Responses were coded into 10 categories capturing strategies GLBTQ parents used to protect their families. While strategies utilizing legal supports were common, the most cited strategies were symbolic strategies, including creating a family name and developing written statements of parent wishes. Exploratory analyses revealed no difference in mean number of strategies used between parents who reported having legal status as a parent through adoption or listing on the birth certificate and those without legal parenting status. These results suggest that GLBTQ parents, regardless of their legal parenting status, take intentional measures to achieve a sense of safety and increase social support. The findings reiterate the importance of both legal and social support of GLBTQ parents.     

Tracking of sport and exercise types from midlife to old age: a 20-year cohort study of British men

Background

Previous physical activity (PA) tracking studies have examined the stability of overall PA and/or PA types, but few have investigated how specific types of sport/exercise track over the life course. The aim of this study was to determine how specific sports/exercises in midlife track and predict future sport/exercise and PA in men transitioning to old age.

Methods

Seven thousand seven hundred thirty-five men (aged 40–59?years) recruited in 1978–80 were followed up after 12, 16 and 20?years. At each wave men self-reported participation in sport/exercise. Frequent sport/exercise participants (>?1/month) reported the types of sport/exercise they engaged in. Men also reported total PA, health status, lifestyle behaviours and socio-demographic characteristics. Stability of each sport/exercise was assessed using kappa statistics and intraclass correlation coefficients. Logistic regression estimated the odds of participating in sport/exercise and being active at 20-year follow up according to specific types of sport/exercise in midlife.

Results

Three thousand three hundred eighty-four men with complete data at all waves were included in analyses. Tracking of specific sports/exercises ranged from fair to substantial, with golf being the most common and most stable. Bowls was the most frequently adopted. Odds of participating in sport/exercise and being active in old age varied according to sport/exercise types in midlife. Golf and bowls in midlife were the strongest predictors of sport/exercise participation in old age. Golf, cricket and running/jogging in midlife were among the strongest predictors of being active in old age. Compared to participating in just one sport/exercise in midlife, sampling multiple sports/exercises was more strongly associated with sport/exercise participation and being active in old age.

Conclusion

The stability of sport/exercise participation from midlife to old age varies by type. Specific sports/exercises in midlife may be more likely to predict future PA than others. However, participating in a range of sports/exercises may be optimal for preserving PA into old age.

     

The exponentiated reduced Kies distribution: Properties and applications

Here we consider an exponentiated version of the reduced Kies distribution and discuss some of its properties. The parameters of the distribution are estimated by the method of maximum likelihood and illustrated with the help of certain real-life data sets. Asymptotic behavior of the maximum likelihood estimators of the parameters of the distribution is also studied by using certain simulated data sets.     

Confidence Corridors for Multivariate Generalized Quantile Regression

We focus on the construction of confidence corridors for multivariate nonparametric generalized quantile regression functions. This construction is based on asymptotic results for the maximal deviation between a suitable nonparametric estimator and the true function of interest, which follow after a series of approximation steps including a Bahadur representation, a new strong approximation theorem, and exponential tail inequalities for Gaussian random fields. As a byproduct we also obtain multivariate confidence corridors for the regression function in the classical mean regression. To deal with the problem of slowly decreasing error in coverage probability of the asymptotic confidence corridors, which results in meager coverage for small sample sizes, a simple bootstrap procedure is designed based on the leading term of the Bahadur representation. The finite-sample properties of both procedures are investigated by means of a simulation study and it is demonstrated that the bootstrap procedure considerably outperforms the asymptotic bands in terms of coverage accuracy. Finally, the bootstrap confidence corridors are used to study the efficacy of the National Supported Work Demonstration, which is a randomized employment enhancement program launched in the 1970s. This article has supplementary materials online.     

The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility

It is well known that in finance variances and covariances of asset returns move together over time. Recently, much interest has been aroused by an approach involving the use of the realized covariance (RCOV) matrix constructed from high-frequency returns as the ex-post realization of the covariance matrix of low-frequency returns. For the analysis of dynamics of RCOV matrices, we propose the generalized conditional autoregressive Wishart (GCAW) model. Both the noncentrality matrix and scale matrix of the Wishart distribution are driven by the lagged values of RCOV matrices, and represent two different sources of dynamics, respectively. The GCAW is a generalization of the existing models, and accounts for symmetry and positive definiteness of RCOV matrices without imposing any parametric restriction. Some important properties such as conditional moments, unconditional moments, and stationarity are discussed. Empirical examples including sequences of daily RCOV matrices from the New York Stock Exchange illustrate that our model outperforms the existing models in terms of model fitting and forecasting.     

Prior specification of neighbourhood and interaction structure in binary Markov random fields

We formulate a prior distribution for the energy function of stationary binary Markov random fields (MRFs) defined on a rectangular lattice. In the prior we assign distributions to all parts of the energy function. In particular we define priors for the neighbourhood structure of the MRF, what interactions to include in the model, and for potential values. We define a reversible jump Markov chain Monte Carlo (RJMCMC) procedure to simulate from the corresponding posterior distribution when conditioned to an observed scene. Thereby we are able to learn both the neighbourhood structure and the parametric form of the MRF from the observed scene. We circumvent evaluations of the intractable normalising constant of the MRF when running the RJMCMC algorithm by adopting a previously defined approximate auxiliary variable algorithm. We demonstrate the usefulness of our prior in two simulation examples and one real data example.     

Improving the detection of unusual observations in high‐dimensional settings

Multivariate control charts are used to monitor stochastic processes for changes and unusual observations. Hotelling's T² statistic is calculated for each new observation and an out‐of‐control signal is issued if it goes beyond the control limits. However, this classical approach becomes unreliable as the number of variables p approaches the number of observations n, and impossible when p exceeds n. In this paper, we devise an improvement to the monitoring procedure in high‐dimensional settings. We regularise the covariance matrix to estimate the baseline parameter and incorporate a leave‐one‐out re‐sampling approach to estimate the empirical distribution of future observations. An extensive simulation study demonstrates that the new method outperforms the classical Hotelling T² approach in power, and maintains appropriate false positive rates. We demonstrate the utility of the method using a set of quality control samples collected to monitor a gas chromatography–mass spectrometry apparatus over a period of 67 days.