Criteria for working-correlation-structure selection in GEE: Assessment via simulation

Efficiency of analysis using generalized estimation equations is enhanced when intracluster correlation structure is accurately modeled. We compare two existing criteria (a quasi-likelihood information criterion, and the Rotnitzky-Jewell criterion) to identify the true correlation structure via simulations with Gaussian or binomial response, covariates varying at cluster or observation level, and exchangeable or AR(l) intracluster correlation structure. Rotnitzky and Jewell's approach performs better when the true intracluster correlation structure is exchangeable, while the quasi-likelihood criteria performs better for an AR(l) structure.

The effect of a self-development coaching program on the psychological health and the academic performance among medical and dental students in Saudi Arabia

Observational studies have shown that medical and dental students have poor psychological health worldwide; however, few interventional studies have been used to test approaches to help students. This thesis used a randomised control trial study design to evaluate the effect of a self-development coaching program on psychological health and the academic performance among medical and dental students in Saudi Arabia. The outcomes indicated that these medical and dental students in Saudi Arabia experienced high levels of depression, anxiety and stress, and that the self-development coaching program was a promising intervention to improve students' psychological health.

Why are students choosing STEM and when do they make their choice?

BACKGROUND OR CONTEXT The higher education sector plays an important role in encouraging students into the STEM pipeline through fostering partnerships with schools, building on universities long tradition in engagement and outreach to secondary schools. Numerous activities focus on integrated STEM learning experiences aimed at developing conceptual scientific and mathematical knowledge with opportunities for students to show and develop skills in working with each other and actively engaging in discussion, decision making and collaborative problem solving. (NAS, 2013; AIG, 2015; OCS, 2014). This highlights the importance of the development and delivery of engaging integrated STEM activities connected to the curriculum to inspire the next generation of scientists and engineers and generally preparing students for post-secondary success. The broad research objective is to gain insight into which engagement activities and to what level they influence secondary school students’ selection of STEM-related career choices at universities. PURPOSE OR GOAL To evaluate and determine the effectiveness of STEM engagement activities impacting student decision making in choosing a STEM-related degree choice at university. APPROACH A survey was conducted with first-year domestic students studying STEM-related fieldswithin the Science and Engineering Faculty at Queensland University of Technology. Of the domestic students commencing in 2015, 29% responded to the survey. The survey was conducted using Survey Monkey and included a variety of questions ranging from academic performance at school to inspiration for choosing a STEM degree. Responses were analysed on a range of factors to evaluate the influence on students’ decisions to study STEM and whether STEM high school engagement activities impacted these decisions. To achieve this the timing of decision making for students choice in study area, degree, and university is compared with the timing of STEM engagement activities. DISCUSSION Statistical analysis using SPSS was carried out on survey data looking at reasons for choosing STEM degrees in terms of gender, academic performance and major influencers in their decision making. It was found that students choose their university courses based on what subjects they enjoyed and exceled at in school. These results found a high correlation between enjoyment of a school subject and their interest in pursuing this subject at university and beyond. Survey results indicated students are heavily influenced by their subject teachers and parents in their choice of STEM-related disciplines. In terms of career choice and when students make their decision, 60% have decided on a broad area of study by year 10, whilst only 15% had decided on a specific course and 10% had decided on which university. The timing of secondary STEM engagement activities is seen as a critical influence on choosing STEM disciplines or selection of senior school subjects with 80% deciding on specific degree between year 11 and 12 and 73% making a decision on which university in year 12. RECOMMENDATIONS/IMPLICATIONS/CONCLUSION Although the data does not support that STEM engagement activities increase the likelihood of STEM-related degree choice, the evidence suggests the students who have participated in STEM activities associate their experiences with their choice to pursue a STEM-related course. It is important for universities to continue to provide quality engaging and inspirational learning experiences in STEM, to identify and build on students’ early interest and engagement, increase STEM knowledge and awareness, engage them in interdisciplinary project-based STEM practices, and provide them with real-world application experiences to sustain their interest.

Eliciting and encoding expert knowledge on variable selection into classical or Bayesian species distribution models

The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

Marker selection by Akaike information criterion and Bayesian information criterion

We carried out a discriminant analysis with identity by descent (IBD) at each marker as inputs, and the sib pair type (affected-affected versus affected-unaffected) as the output. Using simple logistic regression for this discriminant analysis, we illustrate the importance of comparing models with different number of parameters. Such model comparisons are best carried out using either the Akaike information criterion (AIC) or the Bayesian information criterion (BIC). When AIC (or BIC) stepwise variable selection was applied to the German Asthma data set, a group of markers were selected which provide the best fit to the data (assuming an additive effect). Interestingly, these 25-26 markers were not identical to those with the highest (in magnitude) single-locus lod scores.

The moderating effects of job control and selection, optimization, and compensation strategies on the age-work ability relationship

Work ability describes employees' capability to carry out their work with respect to physical and psychological job demands. This study investigated direct and interactive effects of age, job control, and the use of successful aging strategies called selection, optimization, and compensation (SOC) in predicting work ability. We assessed SOC strategies and job control by using employee self-reports, and we measured employees' work ability using supervisor ratings. Data collected from 173 health-care employees showed that job control was positively associated with work ability. Additionally, we found a three-way interaction effect of age, job control, and use of SOC strategies on work ability. Specifically, the negative relationship between age and work ability was weakest for employees with high job control and high use of SOC strategies. These results suggest that the use of successful aging strategies and enhanced control at work are conducive to maintaining the work ability of aging employees. We discuss theoretical and practical implications regarding the beneficial role of the use of SOC strategies utilized by older employees and enhanced contextual resources at work for aging employees.

The buffering effect of selection, optimization, and compensation strategy use on the relationship between problem solving demands and occupational well-being: A daily diary study

This study investigated within-person relationships between daily problem solving demands, selection, optimization, and compensation (SOC) strategy use, job satisfaction, and fatigue at work. Based on conservation of resources theory, it was hypothesized that high SOC strategy use boosts the positive relationship between problem solving demands and job satisfaction, and buffers the positive relationship between problem solving demands and fatigue. Using a daily diary study design, data were collected from 64 administrative employees who completed a general questionnaire and two daily online questionnaires over four work days. Multilevel analyses showed that problem solving demands were positively related to fatigue, but unrelated to job satisfaction. SOC strategy use was positively related to job satisfaction, but unrelated to fatigue. A buffering effect of high SOC strategy use on the demands-fatigue relationship was found, but no booster effect on the demands-satisfaction relationship. The results suggest that high SOC strategy use is a resource that protects employees from the negative effects of high problem solving demands.

Maintaining a focus on opportunities at work: The interplay between age, job complexity, and the use of selection, optimization, and compensation strategies

The concept of focus on opportunities describes how many new goals, options, and possibilities employees believe to have in their personal future at work. This study investigated the specific and shared effects of age, job complexity, and the use of successful aging strategies called selection, optimization, and compensation (SOC) in predicting focus on opportunities. Results of data collected from 133 employees of one company (mean age = 38 years, SD = 13, range 16–65 years) showed that age was negatively, and job complexity and use of SOC strategies were positively related to focus on opportunities. In addition, older employees in high-complexity jobs and older employees in low-complexity jobs with high use of SOC strategies were better able to maintain a focus on opportunities than older employees in low-complexity jobs with low use of SOC strategies.

Influences on novice drivers' speed selection - a systematic review: Application and limitations of theory and methodology

Background Excessive speed is a primary contributing factor to young novice road trauma, including intentional and unintentional speeds above posted limits or too fast for conditions. The objective of this research was to conduct a systematic review of recent investigations into novice drivers’ speed selection, with particular attention to applications and limitations of theory and methodology. Method Systematic searches of peer-reviewed and grey literature were conducted during September 2014. Abstract reviews identified 71 references potentially meeting selection criteria of investigations since the year 2000 into factors that influence (directly or indirectly) actual speed (i.e., behaviour or performance) of young (age <25 years) and/or novice (recently-licensed) drivers. Results Full paper reviews resulted in 30 final references: 15 focused on intentional speeding and 15 on broader speed selection investigations. Both sets identified a range of individual (e.g., beliefs, personality) and social (e.g., peer, adult) influences, were predominantly theory-driven and applied cross-sectional designs. Intentional speed investigations largely utilised self-reports while other investigations more often included actual driving (simulated or ‘real world’). The latter also identified cognitive workload and external environment influences, as well as targeted interventions. Discussion and implications Applications of theory have shifted the novice speed-related literature beyond a simplistic focus on intentional speeding as human error. The potential to develop a ‘grand theory’ of intentional speeding emerged and to fill gaps to understand broader speed selection influences. This includes need for future investigations of vehicle-related and physical environment-related influences and methodologies that move beyond cross-sectional designs and rely less on self-reports.

Selection, optimization, and compensation strategies: Interactive effects on daily work engagement

The theory of selective optimization with compensation (SOC) proposes that the “orchestrated” use of three distinct action regulation strategies (selection, optimization, and compensation) leads to positive employee outcomes. Previous research examined overall scores and additive models (i.e., main effects) of SOC strategies instead of interaction models in which SOC strategies mutually enhance each other's effects. Thus, a central assumption of SOC theory remains untested. In addition, most research on SOC strategies has been cross-sectional, assuming that employees' use of SOC strategies is stable over time. We conducted a quantitative diary study across nine work days (N = 77; 514 daily entries) to investigate interactive effects of daily SOC strategies on daily work engagement. Results showed that optimization and compensation, but not selection, had positive main effects on work engagement. Moreover, a significant three-way interaction effect indicated that the relationship between selection and work engagement was positive only when both optimization and compensation were high, whereas the relationship was negative when optimization was low and compensation was high. We discuss implications for future research and practice regarding the use of SOC strategies at work.

Born leaders: Political selection and the relative age effect in the US Congress

We present substantial evidence for the existence of a bias in the distribution of births of leading US politicians in favour of those who were the eldest in their cohort at school. This result adds to the research on the long-term effects of relative age among peers at school. We discuss parametric and non-parametric tests to identify this effect, and we show that it is not driven by measurement error, redshirting or a sorting effect of highly educated parents. The magnitude of the effect that we estimate is larger than what other studies on ‘relative age effects’ have found for broader populations but is in general consistent with research that looks at professional sportsmen. We also find that relative age does not seem to correlate with the quality of elected politicians.

The first cut is the deepest: Repeated interactions of co-authorship and academic productivity in Nobel laureate teams

Despite much in-depth investigation of factors influencing the co-authorship evolution in various scientific fields, our knowledge about how efficiency or creativity is linked to the longevity of collaborative relationships remains very limited. We explore what Nobel laureates’ co-authorship patterns reveal about the nature of scientific collaborations looking at the intensity and success of scientific collaborations across fields and across laureates’ collaborative lifecycles in physics, chemistry, and physiology/medicine. We find that more collaboration with the same researcher is actually no better for advancing creativity: publications produced early in a sequence of repeated collaborations with a given coauthor tend to be published better and cited more than papers that come later in the collaboration with the same coauthor. Our results indicate that scientific collaboration involves conceptual complementarities that may erode over a sequence of repeated interactions.

Transitioning from university to the workplace: Stakeholder perceptions of academic and professional writing demands

This study provides a detailed insight into the changing writing demands from the last year of university study to the first year in the workforce of engineering and accounting professionals. The study relates these to the demands of the writing component of IELTS, which is increasingly used for exit testing. The number of international and local students whose first language is not English and who are studying in English-medium universities has increased significantly in the past decade. Many of these students aim to start working in the country they studied in; however, some employers have suggested that graduates seeking employment have insufficient language skills. This study provides a detailed insight into the changing writing demands from the last year of university study to the first year in the workforce of engineering and accounting professionals (our two case study professions). It relates these to the demands of the writing component of IELTS, which is increasingly used for exit or professional entry testing, although not expressly designed for this purpose. Data include interviews with final year students, lecturers, employers and new graduates in their first few years in the workforce, as well as professional board members. Employers also reviewed both final year assignments, as well as IELTS writing samples at different levels. Most stakeholders agreed that graduates entering the workforce are underprepared for the writing demands in their professions. When compared with the university writing tasks, the workplace writing expected of new graduates was perceived as different in terms of genre, the tailoring of a text for a specific audience, and processes of review and editing involved. Stakeholders expressed a range of views on the suitability of the use of academic proficiency tests (such as IELTS) as university exit tests and for entry into the professions. With regard to IELTS, while some saw the relevance of the two writing tasks, particularly in relation to academic writing, others questioned the extent to which two timed tasks representing limited genres could elicit a representative sample of the professional writing required, particularly in the context of engineering. The findings are discussed in relation to different test purposes, the intersection between academic and specific purpose testing and the role of domain experts in test validation.

Academic achievement among recently arrived Chinese adolescent migrants: The role of social support, school belonging, and acculturative stress

Factors contributing to academic achievement among recently arrived Chinese adolescents in Australia remains relatively underexplored. Previous studies focused on Asian migrants, including Chinese, but did not distinguish Chinese from other Asian migrants. The current study specifically looks at Chinese migrants who have recently arrived as opposed to Asian migrants. This study aims to explore the role of social support, school belonging, and acculturative stress on academic achievement of recently arrived Chinese adolescents (n = 55). Questionnaires were administered to this sample. The results indicated that school belonging, interestingly, was negatively associated with academic achievement. Perceived social support and acculturative stress were not significantly associated with academic achievement. The findings provide insights into risk and protective factors influencing academic achievement of Chinese migrants. Implications of the findings are discussed.

Reproducibility of scratch assays is affected by the initial degree of confluence: Experiments, modelling and model selection

Scratch assays are difficult to reproduce. Here we identify a previously overlooked source of variability which could partially explain this difficulty. We analyse a suite of scratch assays in which we vary the initial degree of confluence (initial cell density). Our results indicate that the rate of re-colonisation is very sensitive to the initial density. To quantify the relative roles of cell migration and proliferation, we calibrate the solution of the Fisher–Kolmogorov model to cell density profiles to provide estimates of the cell diffusivity, D, and the cell proliferation rate, λ. This procedure indicates that the estimates of D and λ are very sensitive to the initial density. This dependence suggests that the Fisher–Kolmogorov model does not accurately represent the details of the collective cell spreading process, since this model assumes that D and λ are constants that ought to be independent of the initial density. Since higher initial cell density leads to enhanced spreading, we also calibrate the solution of the Porous–Fisher model to the data as this model assumes that the cell flux is an increasing function of the cell density. Estimates of D and λ associated with the Porous–Fisher model are less sensitive to the initial density, suggesting that the Porous–Fisher model provides a better description of the experiments.