TY  - JOUR
PY  - 2022//
TI  - Sampling bias and weight factors for in-depth motorcycle crash data in Thailand
JO  - IATSS research
A1  - Thongnak, Naravit
A1  - Kanitpong, Kunnawee
A1  - Saitoh, Tomofumi
A1  - Lubbe, Nils
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - Motorcycle crashes are documented in Thailand's national records but are underreported and lacking detail. In-depth motorcycle crash data, collected by Thailand Accident Research Center (TARC), contains a smaller number of motorcycle crashes but more detail. However, to draw conclusions at a national level, representativeness of the TARC in-depth data is currently unknown, and the correction of sampling biases may be required. In this study, the Capture-recapture method was used to examine the underreporting in the national crash data (from the government insurance company). It was found that 69% of fatal and 70% of non-fatal injuries were underreported, respectively. The in-depth crash data was found to be biased. The weighting methods post-stratification and iterative proportional fitting were applied to compensate for the bias and are shown to improve the representativeness of the in-depth motorcycle crash data. Weighted in-depth crash data appears to be suitable to draw conclusions on motorcyclist safety in Thailand.<p />  <p>Language: en</p>
LA  - en
SN  - 0386-1112
UR  - http://dx.doi.org/10.1016/j.iatssr.2022.03.002
ID  - ref1
ER  -