Longitudinal shape analysis by using the spherical coordinates

One of the important topics in morphometry that received high attention recently is the longitudinal analysis of shape variation. According to Kendall's definition of shape, the shape of object appertains on non-Euclidean space, making the longitudinal study of configuration somehow difficult. However, to simplify this task, triangulation of the objects and then constructing a non-parametric regression-type model on the unit sphere is pursued in this paper. The prediction of the configurations in some time instances is done using both properties of triangulation and the size of great baselines. Moreover, minimizing a Euclidean risk function is proposed to select feasible weights in constructing smoother functions in a non-parametric smoothing manner. These will provide some proper shape growth models to analysis objects varying in time. The proposed models are applied to analysis of two real-life data sets.     

A study of quadratic inference functions with alternative weighting matrices

Quadratic inference function (QIF) is an alternative methodology to the popular generalized estimating equations (GEE) approach, it does not involve direct estimation of the correlation parameter, and thus remains optimal even if the working correlation structure is misspecified. The idea is to represent the inverse of the working correlation matrix by a linear combination of some basis matrices. In this article, we present a modification of QIF with a robust variance estimator of the extended score function. Theoretical and numerical results show that the modified QIF attains better efficiency and achieves better small sample performance than the original QIF method.     

Comparison of methods for analyzing binary repeated measures data: A simulation-based study (comparison of methods for binary repeated measures)

In this study, some methods suggested for binary repeated measures, namely, Weighted Least Squares (WLS), Generalized Estimating Equations (GEE), and Generalized Linear Mixed Models (GLMM) are compared with respect to power, type 1 error, and properties of estimates. The results indicate that with adequate sample size, no missing data, the only covariate being time effect, and a relatively limited number of time points, the WLS method performs well. The GEE approach performs well only for large sample sizes. The GLMM method is satisfactory with respect to type I error, but its estimates have poorer properties than the other methods.     

Sexual dysfunction predicts depressive symptoms during the first 2 years postpartum

Background

The association between sexual function and depression has yet to be examined in a prospective cohort study with prolonged postpartum follow-up.

Cracking the Code—An Approach to Developing Professional Writing Skills

The development of writing skills sufficient to meet the complexities of contemporary social work practice is a growing demand from employers and practice educators. The paper explores current pedagogical debate relating to student support and the development of writing skills and relates this debate to meeting the needs of social work students engaged in practice learning and professional practice. A number of questions are raised about current social work education in England and the needs of students entering from non-traditional academic backgrounds facing the increasingly rigorous demands of professional report writing. The discussion is then grounded in a practice example of staff from a university social work course and education guidance service working together to meet student need in respect of developing writing skills. The development, implementation and evaluation of a university writing skills programme for social work students are explored. The paper concludes by setting out a range of challenges arising from experience of the programme and a consideration of theory, and points to potential ways forward based on a social practice approach to teaching writing skills.     

Those They Leave Behind: Paternal Incarceration and Maternal Instrumental Support

As the American imprisonment rate has risen, researchers have become increasingly concerned about the implications of mass imprisonment for family life. The authors extend this research by examining how paternal incarceration is linked to perceived instrumental support among the mothers of inmates' children. Results from the Fragile Families and Child Wellbeing Study (N = 4,132) suggest that recent, but not current, paternal incarceration is independently associated with less maternal perceived instrumental support and that this association persists after adjusting for a rich set of control variables, including prior perceived instrumental support. For families of recently incarcerated men, incarceration may be a double strike, simultaneously increasing the need for instrumental support while decreasing its availability when incarcerated fathers return to the community.     

Using agency data for evidence-based programming: a university-agency collaboration

Agencies providing residential treatment are encouraged, or even mandated, to collect outcomes data and to implement evidence based practices, yet little guidance has been provided on how to do so using agency administrative data that are collected on an ongoing basis. We examined data on Child and Adolescent Functional Assessment Scale (CAFAS) scores for 1608 admissions to a residential treatment center from 2002 through 2008. CAFAS scores were measured every 90 days, providing multiple CAFAS scores for each individual. Results demonstrated that on average residents improved in functioning over time. Sensitive to the evolving needs of residents who had been entering the program, the treatment center made significant program changes in 2006 to attempt to better serve residents through a broad array of specialized programming. Compared to the overall results, the analysis suggested that residents who entered the program since October 2006 appeared to have made larger improvements in their CAFAS scores. Results were derived by employing multilevel models appropriate for estimating growth trajectories with repeated measures data. Conversations with agency staff suggested that using administrative data, and advanced statistical models, were extremely helpful for organizational decision making and evidence-based programming.     

Norms,status and the dynamics of advice networks: A case study

The issue of the influence of norms on behavior is as old as sociology itself. This paper explores the effect of normative homophily (i.e. “sharing the same normative choices”) on the evolution of the advice network among lay judges in a courthouse. 0020 and 0025 social exchange theory suggests that members select advisors based on the status of the advisor. Additional research shows that members of an organization use similarities with others in ascribed, achieved or inherited characteristics, as well as other kinds of ties, to mitigate the potentially negative effects of this strong status rule. We elaborate and test these theories using data on advisor choice in the Commercial Court of Paris. We use a jurisprudential case about unfair competition (material and “moral” damages), a case that we submitted to all the judges of this court, to test the effect of normative homophily on the selection of advisors, controlling for status effects. Normative homophily is measured by the extent to which two judges are equally “punitive” in awarding damages to plaintiffs. Statistical analyses combine longitudinal advice network data collected among the judges with their normative dispositions. Contrary to what could be expected from conventional sociological theories, we find no pure effect of normative homophily on the choice of advisors. In this case, therefore, sharing the same norms and values does not have, by itself, a mitigating effect and does not contribute to the evolution of the network. We argue that status effects, conformity and alignments on positions of opinion leaders in controversies still provide the best insights into the relationship between norms, structure and behavior.     

Where do intra-organizational advice relations come from? The role of informal status and social capital in social exchange

Social status and social capital frameworks are used to derive competing hypotheses about the emergence and structure of advice relations in organizations. Although both approaches build on a social exchange framework, they differ in their behavioral micro-foundations. From a status perspective, advice giving is a means to generate prestige, whereas asking advice decreases one's relative standing. At a structural level these motivations are expected to result in an overrepresentation of non-reciprocal dyads and non-cyclical triadic structures in the advice network, as well as in active advice seekers being unlikely to be approached for advice, especially by active advice givers. From a social capital perspective, advice seeking creates obligations for the advice seeker. At the structural level, this results in an overrepresentation of reciprocal dyads and cyclical triads, and active advice seekers to be unpopular as targets of advice seeking, especially for active advice givers. Analyses of four waves of a longitudinal sociometric study of 57 employees of a Dutch Housing Corporation provide partial support for both approaches. In line with the social capital perspective, we find reciprocal advice relations to be overrepresented at the dyad level. Results at the triad level support the social status arguments, according to which high status individuals will avoid asking advice from low status individuals. The implications for macro-structural properties of intra-organizational advice network are discussed.