A likelihood based estimator for vector autoregressive processes

A onestep estimator, which is an approximation to the unconditional maximum likelihood estimator (MLE) of the coefficient matrices of a Gaussian vector autoregressive process is presented. The onestep estimator is easy to compute and can be computed using standard software. Unlike the computation of the unconditional MLE, the computation of the onestep estimator does not require any iterative optimization and the computation is numerically stable. In finite samples the onestep estimator generally has smaller mean square error than the ordinary least squares estimator. In a simple model, where the unconditional MLE can be computed, numerical investigation shows that the onestep estimator is slightly worse than the unconditional MLE in terms of mean square error but superior to the ordinary least squares estimator. The limiting distribution of the onestep estimator for processes with some unit roots is derived.     

On the Assessment of Monte Carlo Error in Simulation-Based Statistical Analyses

Statistical experiments, more commonly referred to as Monte Carlo or simulation studies, are used to study the behavior of statistical methods and measures under controlled situations. Whereas recent computing and methodological advances have permitted increased efficiency in the simulation process, known as variance reduction, such experiments remain limited by their finite nature and hence are subject to uncertainty; when a simulation is run more than once, different results are obtained. However, virtually no emphasis has been placed on reporting the uncertainty, referred to here as Monte Carlo error, associated with simulation results in the published literature, or on justifying the number of replications used. These deserve broader consideration. Here we present a series of simple and practical methods for estimating Monte Carlo error as well as determining the number of replications required to achieve a desired level of accuracy. The issues and methods are demonstrated with two simple examples, one evaluating operating characteristics of the maximum likelihood estimator for the parameters in logistic regression and the other in the context of using the bootstrap to obtain 95% confidence intervals. The results suggest that in many settings, Monte Carlo error may be more substantial than traditionally thought.     

Classification rules for triply multivariate data with an AR(1) correlation structure on the repeated measures over time

In this article we study the problem of classification of three-level multivariate data, where multiple q$q$-variate observations are measured on u$u$-sites and over p$p$-time points, under the assumption of multivariate normality. The new classification rules with certain structured and unstructured mean vectors and covariance structures are very efficient in small sample scenario, when the number of observations is not adequate to estimate the unknown variance–covariance matrix. These classification rules successfully model the correlation structure on successive repeated measurements over time. Computation algorithms for maximum likelihood estimates of the unknown population parameters are presented. Simulation results show that the introduction of sites in the classification rules improves their performance over the existing classification rules without the sites.     

Using conceptual models as a planning and evaluation tool in conservation

Conservation projects are dynamic interventions that occur in complex contexts involving intricate interactions of social, political, economic, cultural, and environmental factors. These factors are constantly changing over time and space as managers learn more about the context within which they work. This complex context poses challenges for planning and evaluating conservation project. In order for conservation managers and evaluation professionals to design good interventions and measure project success, they simultaneously need to embrace and deconstruct contextual complexity.In this article, we describe conceptual models—a tool that helps articulate and make explicit assumptions about a project's context and what a project team hopes to achieve. We provide real-world examples of conceptual models, discuss the relationship between conceptual models and other evaluation tools, and describe various ways that conceptual models serve as a key planning and evaluation tool. These include, for example, that they document assumptions about a project site and they provide a basis for analyzing theories of change.It is impractical to believe that we can completely eliminate detail or dynamic complexity in projects. Nevertheless, conceptual models can help reduce the effects of this complexity by helping us understand it.     

Doing Disability: Disability Formations in the Search for Work*

Disability theorists have spent much time discussing how disability is defined. The theoretical roots for these debates reside in the medical, structural, and minority models of disability. The medical model views disability as equivalent to a functional impairment; the minority model sees a lack of equal rights as a primary impediment to social equality between able and disabled populations; and the structural model looks to environmental factors as the cause of disability. While debates over how to define disability are informative, there is currently an insufficient amount of empirical research looking at how people come to identify themselves as having a disability. Rather than focus on how disability is (or should be) defined, herein we look at how disability identities are constructed as people search for work. We show that people's interactions with employers and employment agencies have important influences on how disability identities are constructed. We borrow from the “doing gender” and “racial formations” paradigms to introduce an interactive approach to looking at how disability identities are constructed. We introduce the concept of disability formation to highlight how disability identities are continually negotiated through interactions with employment agencies and employers. Our findings are based on focus groups with 58 people who self‐identified as having a disability and were working or searching for work.     

Family Structure and Children’s Economic Well-Being: Incorporating Same-Sex Cohabiting Mother Families

Research on family structure and child well-being rarely includes children in same-sex parent families, a notable omission since 28 % of female–female couple households contain children. Using the 2010–2013 pooled current population survey (CPS), we examined children’s economic well-being by family structure. These data were ideal for this study because they included a sizeable number of children in same-sex cohabiting mother families and the CPS measured both official and supplemental poverty, incorporating the cohabiting partner. Using the official poverty measure, children in same-sex cohabiting mother families were more likely to be poor than their counterparts in either different-sex cohabiting or married parent families. Using the supplemental poverty measure, children in same-sex mother families were no more likely to be poor than children in all other types of different-sex two-parent families.     

A Case Study Using Photovoice to Explore Racial and Social Identity Among Young Black Men: Implications for Social Work Research and Practice

This article describes an exploratory qualitative case study using a research method novel to social work known as Photovoice. This case study of the Photovoice process assesses its value as a community-based participatory research (CBPR) method with marginalized communities within social work research. Photovoice was used to engage young Black men as researchers into their own lived experience. Through a photographic and group participatory project, participants discussed how intersections of race, gender, and sexuality affect their lives and health. While this methodology has proliferated within public health literature, little research exists within social work. Photovoice represents a research well-aligned with core social work values of empowerment and social justice. This method offers our profession a participatory, action-oriented tool to inform practice and policy and does so in the voices of communities who often go unheard.     

Factors related to attitudes toward diversity in Australia,Malaysia, and Puerto Rico

In this study, we tested social identity complexity theory (Roccas & Brewer, 2002) in relation to attitudes toward diversity and the associated variables of patriotism, nationalism, religiosity, aggression, and sense of self (well-being) in a cross-cultural study of 398 Malaysian, 239 Australian, and 201 Puerto Rican students. Puerto Ricans reported the most positive attitudes toward diversity, followed by Australians, and finally Malaysians. For Puerto Ricans, pro-diversity attitudes were predicted by a positive correlation with constructive patriotism and a negative correlation with blind patriotism. For Australians, pro-diversity attitudes were predicted by a positive association with constructive patriotism, a negative association with traditional nationalism, and a negative association with physical aggression. For Malaysians, pro-diversity attitudes were predicted by positive relationships with all of the following variables: constructive patriotism, traditional nationalism, verbal aggression, hostility, and the need to bolster self through idealizing others. These results support social identity complexity theory and partially support associated predictions for Australians, Puerto Ricans, and some of the predictions for Malaysians. The results are explained in terms of local cultural contexts that may not easily be understood by a simple understanding of the variables that were measured.     

Understanding barriers to healthy behaviors in black college men

Objective: Due to the short life expectancy of black men, it is important to understand what impacts health behaviors in this group so that interventions and programs can be developed to improve their health behaviors which may help in increasing the life expectancy of black men. The purpose of this study was to understand what perceived barriers exist for black college men that prevent them from engaging in healthy behaviors. Participants and Methods: Thirty-five black male students at a southern Historically Black College and University participated in five focus groups and four interviews. A qualitative analysis was used to analyze data for similar themes and codes. Results: Perceived barriers to engaging in healthy behaviors appear to be influenced by image, food cost, and education. Cues to action for not engaging in healthy behaviors appear to be related to role models. Conclusions: Black college men are not adequately informed or educated about elements that can impact their health and how they can improve it. College administrators and researchers should develop interventions that include elements of increasing health knowledge and age-appropriate role models to improve health behavior change among this group.