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- Flannagan, Carol A.C., et al.
(författare)
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Mutual Recognition Methodology Development
- 2015
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Phase 1 of the Mutual Recognition Methodology Development (MRMD) project developed an approach to statistical modeling and analysis of field data to address the state of evidence relevant to mutual recognition of automotive safety regulations. Specifically, the report describes a methodology that can be used to measure evidence for the hypothesis that vehicles meeting EU safety standards would perform similarly to US-regulated vehicles in the US driving environment, and that vehicles meeting US safety standards would perform similarly to EU-regulated vehicles in the EU driving environment. As part of the project, we assessed the availability and contents of crash datasets from the US and the EU, as well as their collective ability to support the proposed statistical methodology.The report describes a set of three statistical approaches to “triangulate” evidence regarding similarity or differences in crash and injury risk associated with EU- and US-regulated vehicles. Approach 1, Seemingly Unrelated Regression, tests whether the models are identical and will also assess the capability of the data analysis to detect differences in the models, if differences exist.Approach 2, Consequences of Best Models, uses logistic regression to develop two separate models, one for EU risk and one for US risk, as a function of a set of predictors (i.e., crash, vehicle, and occupant conditions). The two models will then be exercised on a standard population for the EU and a standard population for the US. Approach 3, Evidence for Consequences, turns the question aroundto measures the overall evidence for each of a set of possible conclusions. Each conclusion is characterized by a range of relative risk on a single population. Evidence is measured using a weighted average of likelihoods for a large group of models that produce the same outcome. That evidence is then compared using Bayes Factors.
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- Häggström Lundevaller, Erling, 1968-, et al.
(författare)
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Prospects for later-life migration in urban Europe
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Objectives/Aims:Later life migration among the baby boomer generation will have far-reachingimplications of economic development and for planning strategies to ensure adequatehealth, housing and welfare in the right place at the right time. However, much of thecurrent debate about the future trajectory of this type of human mobility has been basedon speculation. The goal of this research is to gain a better understanding of later lifemigration and the likely future trajectory of the retired baby boomers in Europe.The need for more accurate forecasts of future migration flows has increased withthe relative importance of migration vis-à-vis other components of population dynamics.Although forced international migration has been given considerable research attentionin recent years, also other migration types, in particular later-life migration, becomeincreasingly important. In the coming decade, the large baby boom generation will reachretirement age.Methodology/ Results / Findings / Conclusion:The objective of this report is to focus on the effects of an ageing population interms of urban development and retirement migration. The report discusses the regionalpopulation projections and its social impacts. An analysis on the impacts of urbanizationand differential ageing across regions will be given.Moving beyond the simple assumption of a continuation of current trends, anumber of alternative scenarios are explored to simulate the likely future trajectories ofthe baby boomers. Potential impacts on retirement migration caused by changes inaverage retirement age, altered lifestyle preferences and the large size of the baby boomergeneration are considered.
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