Sequential versus simultaneous viewing of an environment : effects of focal attention to individual object locations on visual spatial learning

We investigated memories of room-sized spatial layouts learned by sequentially or simultaneously viewing objects from a stationary position. In three experiments, sequential viewing (one or two objects at a time) yielded subsequent memory performance that was equivalent or superior to simultaneous viewing of all objects, even though sequential viewing lacked direct access to the entire layout. This finding was replicated by replacing sequential viewing with directed viewing in which all objects were presented simultaneously and participants’ attention was externally focused on each object sequentially, indicating that the advantage of sequential viewing over simultaneous viewing may have originated from focal attention to individual object locations. These results suggest that memory representation of object-to-object relations can be constructed efficiently by encoding each object location separately, when those locations are defined within a single spatial reference system. These findings highlight the importance of considering object presentation procedures when studying spatial learning mechanisms.

A disaggregate discrete choice model of transportation demand by elderly and disabled people in rural Virginia

This paper uses a correlated multinomial logit model and a Poisson regression model to measure the factors affecting demand for different types of transportation by elderly and disabled people in rural Virginia. The major results are: (a) A paratransit system providing door-to-door service is highly valued by transportation-handicapped people; (b) Taxis are probably a potential but inferior alternative even when subsidized; (c) Buses are a poor alternative, especially in rural areas where distances to bus stops may be long; (d) Making buses handicap-accessible would have a statistically significant but small effect on mode choice; (e) Demand is price inelastic; and (f) The total number of trips taken is insensitive to mode availability and characteristics. These results suggest that transportation-handicapped people take a limited number of trips. Those they do take are in some sense necessary (given the low elasticity with respect to mode price or availability). People will substitute away from relying upon others when appropriate transportation is available, at least to some degree. But such transportation needs to be flexible enough to meet the needs of the people involved.

Two dynamic discrete choice estimation problems and simulation method solutions

This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results.

Fertility choice, land, and the Malthusian hypothesis

In a standard overlapping generations growth model, with a fixed amount of land and endogenous fertility, the competitive economy converges to a steady state with a zero population growth rate and positive consumption per capita. The Malthusian hypothesis is interpreted as a positive statement about the relationship between population growth and consumption per-capita, when production exhibits diminishing returns to labor and there is a fixed amount of land essential for production. Even when individuals care only about the number of their children and not about their children's welfare, the equilibrium is such that they eventually would choose to have only one child for each adult. Hence, if Malthus's "positive check' on population is the result of the response of optimizing agents to competitively determined prices, Malthus's pessimistic conjecture is not necessarily true, even though his other assumptions hold. -from Authors

Use your freedom of choice : reasons for choosing homeschool in Australia

In Australia, the decision to home educate is becoming increasingly popular (cf. Harding & Farrell, 2003; Townsend, 2012). In spite of its increasing popularity, the reasons home education is chosen by Australian families is under-researched (cf. Jackson & Allan, 2010). This paper reports on a case study that set out to explore the links between families that unschool and the parenting philosophies they follow. In- depth, qualitative interviews were conducted with a group of home education families in one of Australia’s most populated cities. Data were analysed using Critical Discourse Analysis. The analysis revealed that there were links between the parents’ beliefs about home education and their adherence to Attachment Parenting.

Sequential monitoring of hospital adverse events when control charts fail : the example of fall injuries in hospitals

Objective To evaluate methods for monitoring monthly aggregated hospital adverse event data that display clustering, non-linear trends and possible autocorrelation. Design Retrospective audit. Setting The Northern Hospital, Melbourne, Australia. Participants 171,059 patients admitted between January 2001 and December 2006. Measurements The analysis is illustrated with 72 months of patient fall injury data using a modified Shewhart U control chart, and charts derived from a quasi-Poisson generalised linear model (GLM) and a generalised additive mixed model (GAMM) that included an approximate upper control limit. Results The data were overdispersed and displayed a downward trend and possible autocorrelation. The downward trend was followed by a predictable period after December 2003. The GLM-estimated incidence rate ratio was 0.98 (95% CI 0.98 to 0.99) per month. The GAMM-fitted count fell from 12.67 (95% CI 10.05 to 15.97) in January 2001 to 5.23 (95% CI 3.82 to 7.15) in December 2006 (p<0.001). The corresponding values for the GLM were 11.9 and 3.94. Residual plots suggested that the GLM underestimated the rate at the beginning and end of the series and overestimated it in the middle. The data suggested a more rapid rate fall before 2004 and a steady state thereafter, a pattern reflected in the GAMM chart. The approximate upper two-sigma equivalent control limit in the GLM and GAMM charts identified 2 months that showed possible special-cause variation. Conclusion Charts based on GAMM analysis are a suitable alternative to Shewhart U control charts with these data.

Public preferences for biodiversity conservation and climate-change mitigation: A choice experiment using ecosystem services indicators

Potential conflicts exist between biodiversity conservation and climate-change mitigation as trade-offs in multiple-use land management. This study aims to evaluate public preferences for biodiversity conservation and climate-change mitigation policy considering respondents’ uncertainty on their choice. We conducted a choice experiment using land-use scenarios in the rural Kushiro watershed in northern Japan. The results showed that the public strongly wish to avoid the extinction of endangered species in preference to climate-change mitigation in the form of carbon sequestration by increasing the area of managed forest. Knowledge of the site and the respondents’ awareness of the personal benefits associated with supporting and regulating services had a positive effect on their preference for conservation plans. Thus, decision-makers should be careful about how they provide ecological information for informed choices concerning ecosystem services tradeoffs. Suggesting targets with explicit indicators will affect public preferences, as well as the willingness of the public to pay for such measures. Furthermore, the elicited-choice probabilities approach is useful for revealing the distribution of relative preferences for incomplete scenarios, thus verifying the effectiveness of indicators introduced in the experiment.

Modal choice between air and rail : a social efficiency benchmarking analysis that considers CO2 emissions

The problem of modal choice between rail and air arises as public awareness of carbon dioxide (CO2) emissions by the transportation sector rises. In this paper, we answer this question quantitatively by performing an efficiency benchmarking analysis that takes into account life-cycle CO2 emission due to transport service provision. The paper employs nonparametric efficiency estimation methods, namely a slacks-based inefficiency measure, as well as a more conventional directional distance function approach. We apply them to a panel data set for three major railway companies and the aviation sector in Japan for the period from 1999 to 2007. Results shows that, contrary to the common argument, air transport can still be more socially efficient than rail transport, even when the environmental load due to CO2 emission is incorporated. This is due to the aviation sector's extremely low user cost, measured in terms of in-vehicle time. In other words, aviation is a necessary transportation mode for those with a very high willingness to pay for their time.

The choice of spatial scales and spatial smoothness priors for various spatial patterns

Given the drawbacks for using geo-political areas in mapping outcomes unrelated to geo-politics, a compromise is to aggregate and analyse data at the grid level. This has the advantage of allowing spatial smoothing and modelling at a biologically or physically relevant scale. This article addresses two consequent issues: the choice of the spatial smoothness prior and the scale of the grid. Firstly, we describe several spatial smoothness priors applicable for grid data and discuss the contexts in which these priors can be employed based on different aims. Two such aims are considered, i.e., to identify regions with clustering and to model spatial dependence in the data. Secondly, the choice of the grid size is shown to depend largely on the spatial patterns. We present a guide on the selection of spatial scales and smoothness priors for various point patterns based on the two aims for spatial smoothing.

Influence of visible work activity on drivers’ speed choice at roadworks

Vehicle traffic through roadwork sites creates a hazardous work environment, with speed limit noncompliance a major contributor to the high risk and high severity of roadwork crashes. This paper examines responses to an online survey to better understand the factors underlying drivers’ work zone speed choices. Drivers’ stated speed choice was compared between two photographs of the same work zone section – one with workers and machinery present and another with no visible activity. Drivers also provided comments on any aspect of roadwork safety they thought was important. A paired t-test of stated speed choice revealed that significantly lower mean speeds were nominated when workers and machinery were clearly present and active (41.7 vs 53.5 km/h, p<0.01). Participants expressed concern about roadwork signage and reduced speed limits being left in place when there was no apparent work activity. Driver perceptions, and thus compliance, may be improved through technological and operational changes.

Influence of cytochrome P-450 inhibitors on the inhalative uptake of methyl chloride and methylene chloride in male B6C3F1 mice

Dichloromethane (DCM) is thought to be metabolized in vivo by two independent pathways: a glutathione (GSH) dependent pathway that yields CO2 and a cytochrome P-450 mediated one that yields both CO and CO2 (Gargas et al 1986). With a physiologically based pharmacokinetic (PB-PK) model, Andersen et al (1987) calculate the quantitative parameters for both metabolic pathways. Using the kinetic parameters thus obtained and the results of two carcinogenicity studies with rodents (Serota et al 1986; NTP 1985), the authors then estimate the tumour risk for humans.

Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets

Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.