Multivariate logistic regression for familial aggregation in age at disease onset

Familial aggregation studies seek to identify diseases that cluster in families. These studies are often carried out as a first step in the search for hereditary factors affecting the risk of disease. It is necessary to account for age at disease onset to avoid potential misclassification of family members who are disease-free at the time of study participation or who die before developing disease. This is especially true for late-onset diseases, such as prostate cancer or Alzheimer's disease. We propose a discrete time model that accounts for the age at disease onset and allows the familial association to vary with age and to be modified by covariates, such as pedigree relationship. The parameters of the model have interpretations as conditional log-odds and log-odds ratios, which can be viewed as discrete time conditional cross hazard ratios. These interpretations are appealing for cancer risk assessment. Properties of this model are explored in simulation studies, and the method is applied to a large family study of cancer conducted by the National Cancer Institute-sponsored Cancer Genetics Network (CGN).     

Random change point models: investigating cognitive decline in the presence of missing data

With the aim of identifying the age of onset of change in the rate of cognitive decline while accounting for the missing observations, we considered a selection modelling framework. A random change point model was fitted to data from a population-based longitudinal study of ageing (the Cambridge City over 75 Cohort Study) to model the longitudinal process. A missing at random mechanism was modelled using logistic regression. Random effects such as initial cognitive status, rate of decline before and after the change point, and the age of onset of change in rate of decline were estimated after adjustment for risk factors for cognitive decline. Among other possible predictors, the last observed cognitive score was used to adjust the probability of death and dropout. Individuals who experienced less variability in their cognitive scores experienced a change in their rate of decline at older ages than individuals whose cognitive scores varied more.     

Occupation as refrain: territory and beyond in Occupy London

Emerging with the wider ‘movements of the squares’ of 2011, Occupy London was defined by occupation, and by participants’ negotiation of what occupation meant. Its forms and meanings changed as London’s Occupiers moved between occupied sites, through uprootings by eviction, and into post-eviction attempts to extend Occupy’s territorial politics without the camps. This paper builds on three years of ethnography to consider occupation as an unfolding process, using Deleuze and Guattari’s concept of the ‘refrain’. This describes territory in three ‘moments’: the marking of a fragile centre; the stabilization of a bounded ‘home’; and the breaching of boundaries, extending in progressive directions. This rubric is used to analyze London’s occupations, and their defining tension, between an expansive desire to ‘Occupy Everywhere’ – connecting to the wider ‘99 percent’ – and the tendency to become embedded in the protest camp ‘home’. The features of ‘home’ are analyzed using Foucault’s concept of ‘heterotopia’, highlighting an alterity with ambivalent consequences for Occupy’s project. The paper argues that despite a desire to ‘deterritorialize’ occupation, Occupy London stalled in the moment of ‘home’, a consequence of the camp’s status as the ‘common ground’ of an often disparate movement, and the reduction of productive capacities characterizing Occupy’s terminal downswing.     

Human land use as a driver of plant community composition in wetlands of the Chicago metropolitan region

Anthropogenic alteration of the landscape has facilitated plant community change and non-native species invasion in urban areas. We used species occurrence data from over 2000 wetlands within the Chicago metropolitan region to classify urban wetlands into community types and examined non-native species composition across community types. Non-native species were widespread across the region, occurring in over 99% of wetlands. On average, 35% of the plant species in individual wetlands were non-native. A single non-native species, Phalaris arundinacea, was present in 74% of wetlands. Six wetland community types were identified (wet meadows, marshes, forested wetlands, farmed wetlands/mudflats, roadside marshes, and an undetermined wetland type), with each having aggressively spreading non-natives amongst the most common plant species. We conducted canonical correspondence analysis to evaluate the contribution of surrounding land cover, roads, and location of wetlands to plant community composition in these wetlands, and found that similar changes to the landscape have resulted in similar combinations of native and non-native species. Differences in species composition reflected spatial gradients in land use from urban to rural areas across the region, as well as proximity to major roads. Anthropogenic drivers have resulted in profound and pervasive changes to wetland communities across the region, creating novel habitats and ultimately novel community types.     

Advancing Risk‐Informed Decision Making in Managing Defense Nuclear Waste in the United States: Opportunities and Challenges for Risk Analysis

An omnibus spending bill in 2014 directed the Department of Energy to analyze how effectively Department of Energy (DOE) identifies, programs, and executes its plans to address public health and safety risks that remain as part of DOE's remaining environmental cleanup liabilities. A committee identified two dozen issues and associated recommendations for the DOE, other federal agencies, and the U.S. Congress to consider, as well as other stakeholders such as states and tribal nations. In regard to risk assessment, the committee described a risk review process that uses available data, expert experience, identifies major data gaps, permits input from key stakeholders, and creates an ordered set of risks based on what is known. Probabilistic risk assessments could be a follow‐up from these risk reviews. In regard to risk management, the states, in particular, have become major drivers of how resources are driven. States use different laws, different priorities, and challenge DOE's policies in different ways. Land use decisions vary, technology choices are different, and other notable variations are apparent. The cost differences associated with these differences are marked. The net result is that resources do not necessarily go to the most prominent human health and safety risks, as seen from the national level.     

Moving Towards the Post p < 0.05 Era via the Analysis of Credibility

ABSTRACT

It is now widely accepted that the techniques of null hypothesis significance testing (NHST) are routinely misused and misinterpreted by researchers seeking insight from data. There is, however, no consensus on acceptable alternatives, leaving researchers with little choice but to continue using NHST, regardless of its failings. I examine the potential for the Analysis of Credibility (AnCred) to resolve this impasse. Using real-life examples, I assess the ability of AnCred to provide researchers with a simple but robust framework for assessing study findings that goes beyond the standard dichotomy of statistical significance/nonsignificance. By extracting more insight from standard summary statistics while offering more protection against inferential fallacies, AnCred may encourage researchers to move toward the post p?<?0.05 era.     

Behavior-Based Safety in a Coal Mine: The Relationship Between Observations,Participation, and Injuries Over a 14-Year Period

Safety is an important topic in the inherently dangerous mining industry. The creation of a behavior-based safety program and improved employee-management relationships reduced incident rates by 50%. The safety program focused on employee observations and oversight from steering committees. This case study suggests that participation rates of 30% could produce mine-wide safety improvement and considers possible explanations in the context of current literature and anecdotal reports.     

A Comparison of Two Data Analysis Training Methods for Paraprofessionals in an Educational Setting

Analyzing and using student educational data to guide instructional programming is a critical staff skill to ensure quality programming based on applied behavior analysis. We compared two training methods to teach staff to use rules to analyze graphed educational data to enact program changes: didactic instruction and behavioral skills training using direct practice. Participants showed improvements in verbally identifying data patterns using simulated data; however, participants in the latter group were also effective using actual student data. The lack of correspondence between rule identification and rule following challenges the assumption that an individual’s ability to identify rules predicts actual performance.