Day: December 1, 2010

The Built Environment and Motor Vehicle Ownership and Use: Evidence from Santiago de Chile

/ Matt Artz / 1 Comment

Urban Studies, July 2010; vol. 47, 8: pp. 1793-1817., first published on February 23, 2010

Christopher Zegras

“This paper examines the relationships between the built environment—both ‘neighborhood’ design characteristics and relative location—and motor vehicle ownership and use in a rapidly motorising, developing city context, that of Santiago de Chile. A vehicle choice model suggests that income dominates the household vehicle ownership decision, but also detects a relationship between several built environment characteristics and a household’s likelihood of car ownership. A second model, directly linked to the ownership model to correct for selection bias and endogeneity, suggests a strong relationship with locational characteristics like distance to the central business district and Metro stations. Elasticities of vehicle kilometres travelled (VKT), calculated via the combined models, suggest that income plays the overall largest single role in determining VKT. In combination, however, a range of different design and relative location characteristics also display a relatively strong association with VKT.”

Small Area Estimation of Sparse Disease Counts using Shared Component Models–Application to Birth Defect Registry Data in New South Wales, Australia

/ Matt Artz

Health & Place, Volume 16, Issue 4, July 2010, Pages 684-693

Arul Earnest, John R. Beard, Geoff Morgan, Douglas Lincoln, Richard Summerhayes, Deborah Donoghue, Therese Dunn, David Muscatello, and Kerrie Mengersen

“In the field of disease mapping, little has been done to address the issue of analysing sparse health datasets. We hypothesised that by modelling two outcomes simultaneously, one would be able to better estimate the outcome with a sparse count. We tested this hypothesis utilising Bayesian models, studying both birth defects and caesarean sections using data from two large, linked birth registries in New South Wales from 1990 to 2004. We compared four spatial models across seven birth defects: spina bifida, ventricular septal defect, OS atrial septal defect, patent ductus arteriosus, cleft lip and or palate, trisomy 21 and hypospadias. For three of the birth defects, the shared component model with a zero-inflated Poisson (ZIP) extension performed better than other simpler models, having a lower deviance information criteria (DIC). With spina bifida, the ratio of relative risk associated with the shared component was 2.82 (95% CI: 1.46–5.67). We found that shared component models are potentially beneficial, but only if there is a reasonably strong spatial correlation in effect for the study and referent outcomes.”

The Direct Sampling Method to Perform Multiple-point Geostatistical Simulations

/ Matt Artz

Water Resources Research, Vol. 46, W11536, 14 pp., 2010

Gregoire Mariethoz, Philippe Renard, Julien Straubhaar

“Multiple-point geostatistics is a general statistical framework to model spatial fields displaying a wide range of complex structures. In particular, it allows controlling connectivity patterns that have a critical importance for groundwater flow and transport problems. This approach involves considering data events (spatial arrangements of values) derived from a training image (TI). All data events found in the TI are usually stored in a database, which is used to retrieve conditional probabilities for the simulation. Instead, we propose to sample directly the training image for a given data event, making the database unnecessary. Our method is statistically equivalent to previous implementations, but in addition it allows extending the application of multiple-point geostatistics to continuous variables and to multivariate problems. The method can be used for the simulation of geological heterogeneity, accounting or not for indirect observations such as geophysics. We show its applicability in the presence of complex features, nonlinear relationships between variables, and with various cases of nonstationarity. Computationally, it is fast, easy to parallelize, parsimonious in memory needs, and straightforward to implement.”