These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Nonresponse analysis and adjustment in a mail survey on car accidents. Author: Tivesten E, Jonsson S, Jakobsson L, Norin H. Journal: Accid Anal Prev; 2012 Sep; 48():401-15. PubMed ID: 22664706. Abstract: Statistical accident data plays an important role for traffic safety development involving the road system, vehicle design, and driver education. Vehicle manufacturers use data from accident mail surveys as an integral part of the product development process. Low response rates has, however, lead to concerns on whether estimates from a mail survey can be trusted as a source for making strategic decisions. The main objective of this paper was to investigate nonresponse bias in a mail survey addressing driver behaviour in accident situations. Insurance data, available for both respondents and nonrespondents were used to analyze, as well as adjust for nonresponse. Response propensity was investigated by using descriptive statistics and logistic regression analyses. The survey data was then weighted by using inverse propensity weights. Two specific examples of survey estimates are addressed, namely driver vigilance and driver's distraction just before the accident. The results from this paper reveal that driver age and accident type were the most influential variables for nonresponse weighting. Driver gender and size of town where the driver resides also had some influence, but not for all survey variables investigated. The main conclusion of this paper is that nonresponse weighting can increase confidence in accident data collected by a mail survey, especially when response rates are low. Weighting has a moderate influence on this survey, but a larger influence may be expected if applied on a more diverse driver population. The development of auxiliary data collection can further improve accident mail survey methodology in future.[Abstract] [Full Text] [Related] [New Search]