The promoting adult resilience (PAR) program : the effectiveness of the second, shorter pilot of a workplace prevention program

This article details the second, successful pilot of the Promoting Adult Resilience (PAR) program in the human-services departments of a local government organization. The PAR program is a strengths-based resilience building program that integrates Interpersonal and CBT perspectives and this pilot use a shorter, 7-week version of the program. Pre, post and follow-up measures on PAR participants from a resource-sector company were compared with a non-intervention matched comparison group. Post-test, PAR participants reported greater self-efficacy, more family satisfaction, greater f\work-life fit and balance and less negative family to work spillover than the comparison group. At the 6-month follow-up, these gains were maintained to a lesser degree, although work-life balance was strengthened, and negative spillover in both directions reduced. Participants also reported greater optimism for the future, greater work satisfaction and promisingly for human service workers, exhaustion was reduced and more vigour, important for human services as burnout, exhaustion is part of this is a serious work hazard

Bootstrap approaches for estimation and confidence intervals of long term memory processes

In this work, we investigate an alternative bootstrap approach based on a result of Ramsey [F.L. Ramsey, Characterization of the partial autocorrelation function, Ann. Statist. 2 (1974), pp. 1296-1301] and on the Durbin-Levinson algorithm to obtain a surrogate series from linear Gaussian processes with long range dependence. We compare this bootstrap method with other existing procedures in a wide Monte Carlo experiment by estimating, parametrically and semi-parametrically, the memory parameter d. We consider Gaussian and non-Gaussian processes to prove the robustness of the method to deviations from normality. The approach is also useful to estimate confidence intervals for the memory parameter d by improving the coverage level of the interval.

On PAR : Using Participatory Action Research to Improve Early Intervention

This manual is designed to assist human service practitioners and agencies, and the communities they work with, to enhance their skills in undertaking Participatory Action Research, and, in so doing improve the situations of people who are vulnerable. It utilises insights derived from a number of Australian Government funded programs, most notably Reconnect, NAYSS and Household Organisational Management Expenses (HOME) Advice.

Operational performance of low-cost carriers and international airlines : New evidence using a bootstrap truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil. At the same time, the European airline industry entered a period of substantive deregulation. This period witnessed opportunities for low-cost carriers to become more competitive in the market as a result of these combined events. To help assess airline performance in the aftermath of these events, this paper provides new evidence of technical efficiency for 42 national and international airlines in 2006 using the data envelopment analysis (DEA) bootstrap approach first proposed by Simar and Wilson (J Econ, 136:31-64, 2007). In the first stage, technical efficiency scores are estimated using a bootstrap DEA model. In the second stage, a truncated regression is employed to quantify the economic drivers underlying measured technical efficiency. The results highlight the key role played by non-discretionary inputs in measures of airline technical efficiency.

Efficiency of research performance of Australian universities : a reappraisal using a bootstrap truncated regression approach

The motivation of the study stems from the results reported in the Excellence in Research for Australia (ERA) 2010 report. The report showed that only 12 universities performed research at or above international standards, of which, the Group of Eight (G8) universities filled the top eight spots. While performance of universities was based on number of research outputs, total amount of research income and other quantitative indicators, the measure of efficiency or productivity was not considered. The objectives of this paper are twofold. First, to provide a review of the research performance of 37 Australian universities using the data envelopment analysis (DEA) bootstrap approach of Simar and Wilson (2007). Second, to determine sources of productivity drivers by regressing the efficiency scores against a set of environmental variables.

PAR/RAP : Action Research/Research Action Participation

This is a creative piece inspired within and by the decolonising stream that emerged at the World Congress on Action Research and Action Learning, held in Melbourne, Australia in September 2010. It compliments the other works within ALAR Journal's specific edition on research experiences within the decolonising space.

Promoting Adult Resilience (PAR): Group Leaders Manual

RAP-A was developed to meet the need for a universal resilience building program for teenagers which could be readily implemented in a school setting. A universal program targets all teenagers in a particular grade as opposed to those at higher risk for depression (indicated or selective approaches) or a treatment group. It is easier to recruit and engage adolescents in a universal approach where students do not face the risk of stigmatisation by being singled out for intervention. The Resourceful Adolescent Program (RAP: Shochet, Holland & Whitefield, 1997) was developed to meet this need.

Promoting Adult Resilience (PAR): Participant Workbook

The RAP-A Workbook comprises all of the handouts required for the program's individual and group activities. A Participant Workbook is required for each adolescent to write in, and keep at the end of the program.

Technical efficiency of mainstream airlines and low-cost carriers : New evidence using bootstrap data envelopment analysis truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.

Bayesian parametric bootstrap for models with intractable likelihoods

In this paper it is demonstrated how the Bayesian parametric bootstrap can be adapted to models with intractable likelihoods. The approach is most appealing when the semi-automatic approximate Bayesian computation (ABC) summary statistics are selected. After a pilot run of ABC, the likelihood-free parametric bootstrap approach requires very few model simulations to produce an approximate posterior, which can be a useful approximation in its own right. An alternative is to use this approximation as a proposal distribution in ABC algorithms to make them more efficient. In this paper, the parametric bootstrap approximation is used to form the initial importance distribution for the sequential Monte Carlo and the ABC importance and rejection sampling algorithms. The new approach is illustrated through a simulation study of the univariate g-and- k quantile distribution, and is used to infer parameter values of a stochastic model describing expanding melanoma cell colonies.

Smooth bootstrap methods for analysis of longitudinal data

In analysis of longitudinal data, the variance matrix of the parameter estimates is usually estimated by the 'sandwich' method, in which the variance for each subject is estimated by its residual products. We propose smooth bootstrap methods by perturbing the estimating functions to obtain 'bootstrapped' realizations of the parameter estimates for statistical inference. Our extensive simulation studies indicate that the variance estimators by our proposed methods can not only correct the bias of the sandwich estimator but also improve the confidence interval coverage. We applied the proposed method to a data set from a clinical trial of antibiotics for leprosy.