The Gudaga Research Program: A Case Study in Undertaking Research with an Urban Aboriginal Community

This paper presents the Gudaga Research Program as a case study describing the practice principles used to implement a successful research partnership with an urban Aboriginal community in south-western Sydney. This is one of few papers that address research issues unique to working with urban Aboriginal communities, in which the Aboriginal culture of the community is not homogenous. The authors argue that the relationships between the researchers and key community members and research participants underpin the research success. Throughout, the authors show that ongoing processes to nurture and reaffirm these relationships are important and require ongoing investment. A proposed practice framework demonstrates the relationship between knowledge and understanding of Aboriginal history and culture, the underpinning values including trust, respect, and reciprocity, and shared skills and communication. Examples of how these were built into the research are provided. These are important skills that have application beyond the research process.     

Exploring the Nexus of Nonprofit Financial Stability and Financial Growth

Taking a unified approach to studying nonprofit financial health, this research tackles a key question that has remained unexplored in the literature: “What lies at the intersection of the two key dimensions of financial health–financial stability and financial growth?” Specifically, we identify and compare nonprofits that exhibit high levels of financial stability and growth (high financially performing) to those that exhibit low levels (low financially performing)? Overall, we find that high financial performers (HFPs) tend to be older and larger organizations (in terms of unrestricted net assets and total revenue). HFPs are also more likely to report capital assets, and report high levels of compensation. Finally, HFPs tend to contain their overhead spending by exercising efficiency by investing in talented officers (paying more than the rest), but limiting the share of officer compensation, administrative, and fundraising expenses, as a percentage of total expenses. The results of the study should be informative to stakeholders attempting to understand the profile of an organization that is successfully able to achieve both capacity growth and financial stability.     

Parental supervision and adolescent risky behaviors

This paper re-examines the relationship between parental supervision and adolescents’ engagement in risky behaviors. Using the Child Development Supplement and Transition to Adulthood of the Panel Study of Income Dynamics, I consider different measures of supervision among a sample of adolescents 10–21 years old. Issues relating to endogeneity bias and unobserved heterogeneity are accounted for using lagged amounts of supervision and fixed effects as an estimation strategy. The results highlight the role of fathers in mitigating cigarette smoking in the past month, regular alcohol consumption in the past year, and marijuana smoking in the past month. The research emphasizes the need to account for unobserved heterogeneity and supports the idea of looking at the different roles of each parent in affecting child outcomes.     

Bent‐cable regression with autoregressive noise

Motivated by time series of atmospheric concentrations of certain pollutants the authors develop bent‐cable regression for autocorrelated errors. Bent‐cable regression extends the popular piecewise linear (broken‐stick) model, allowing for a smooth change region of any non‐negative width. Here the authors consider autoregressive noise added to a bent‐cable mean structure, with unknown regression and time series parameters. They develop asymptotic theory for conditional least‐squares estimation in a triangular array framework, wherein each segment of the bent cable contains an increasing number of observations while the autoregressive order remains constant as the sample size grows. They explore the theory in a simulation study, develop implementation details, apply the methodology to the motivating pollutant dataset, and provide a scientific interpretation of the bent‐cable change point not discussed previously. The Canadian Journal of Statistics 38: 386–407; 2010 © 2010 Statistical Society of Canada     

A robust pairwise likelihood method for incomplete longitudinal binary data arising in clusters

Clustered longitudinal data feature cross‐sectional associations within clusters, serial dependence within subjects, and associations between responses at different time points from different subjects within the same cluster. Generalized estimating equations are often used for inference with data of this sort since they do not require full specification of the response model. When data are incomplete, however, they require data to be missing completely at random unless inverse probability weights are introduced based on a model for the missing data process. The authors propose a robust approach for incomplete clustered longitudinal data using composite likelihood. Specifically, pairwise likelihood methods are described for conducting robust estimation with minimal model assumptions made. The authors also show that the resulting estimates remain valid for a wide variety of missing data problems including missing at random mechanisms and so in such cases there is no need to model the missing data process. In addition to describing the asymptotic properties of the resulting estimators, it is shown that the method performs well empirically through simulation studies for complete and incomplete data. Pairwise likelihood estimators are also compared with estimators obtained from inverse probability weighted alternating logistic regression. An application to data from the Waterloo Smoking Prevention Project is provided for illustration. The Canadian Journal of Statistics 39: 34–51; 2011 © 2010 Statistical Society of Canada     

Iraqi IDPs Access to Durable Solutions: Results of Two Rounds of a Longitudinal Study

This article discusses the findings from a 4,000 household, longitudinal study conducted by the International Organization for Migration (IOM) and Georgetown University. Using the Inter‐Agency Standing Committee (IASC) Framework on Durable Solutions, we investigate the circumstances in which households were displaced, and how their needs, strategies, and access to durable solutions change over time as they integrate, return, or settle elsewhere. Findings from the study thus allow us to build an evidence base that helps researchers and policymakers to move beyond conceptions of displacement as either a ‘crisis’ or a problem that has been solved, and instead bring into focus the ways in which displaced people find ways to rebuild their lives and livelihoods that coexist alongside patterns of mobility and risk management.     

Correction to: Investigating demographic processesusing innovative combinations of remotelysensed and demographic data

Population and Environment - The original version of this article unfortunately contained a mistake. The name “Kluger” in the second paragraph should be changed to “Kugler”.     

Job Decision Latitude Lowers Worker Stress,but for Whom? Results from the National Longitudinal Study of Adolescent to Adult Health

Population Research and Policy Review - Prior research shows job decision latitude is associated with stress. Few studies of this association address omitted-variable bias or how employee gender...     

Parametric and semiparametric estimation methods for survival data under a flexible class of models

Lifetime Data Analysis - In survival analysis, accelerated failure time models are useful in modeling the relationship between failure times and the associated covariates, where covariate effects...