Download Angmar (Middle Earth Role Playing MERP #2018) by H. Kubash, G. Staplehurst, Graham Staplehurst, Heike PDF

By H. Kubash, G. Staplehurst, Graham Staplehurst, Heike Kubasch, Suzanne Young

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Transportation Research Part F: Traffic psychology and Behaviour 4, 271–277. , & Simmons, L. (2003). The distraction effects of phone use during a crucial driving manoeuvre. Accident Analysis and Prevention, 35, 501–514. , & O’Neill, M. (2005). Self-enhancement, crash-risk optimism and the impact of safety advertisements on young drivers. British Journal of Psychology, 96, 215–230. , & Burg, A. (1977). A reanalysis of Californian driver vision data: general findings. (TRRL Laboratory Report 768) Crowthorne, Berkshire: Transport and Road Research Laboratory.

One reason for this is that the data for the two variables being correlated (personality measure and collision rate) are so “noisy” that any underlying relationship is likely to be masked. Personality traits are normally measured by questionnaires, and these are a rather crude tool. Collisions usually have multiple causes, and personality factors may be only the starting point in a chain of events culminating in a collision. Another reason is that ascribing riskiness to single personality factors may be too simplistic.

Journal of Safety Research, 34, 71–77. , & Marom, Y. (2001). Novice drink drivers, recidivism and crash involvement. Accident Analysis and Prevention, 33(2), 221–227. Folkard, S. (1997). Black times: Temporal determinants of transport safety. Accident Analysis and Prevention, 29, 417–430. , & Font-Mayolas, S. (2007). Mobile phone use while driving in a sample of Spanish university workers. Accident Analysis and Prevention, 39(2), 347–355. M. (1994). Risk of accidents among elderly car drivers with visual acuity equal to 6/12 or 6/15 and lack of binocular vision.

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