TY  - JOUR
PY  - 2021//
TI  - Exploring temporal interactions of crash counts in California using distinct log-linear contingency table models
JO  - International journal of injury control and safety promotion
A1  - Cheng, Wen
A1  - Singh, Mankirat
A1  - Clay, Edward
A1  - Kwong, Jerry
A1  - Cao, Menglu
A1  - Li, Yihua
A1  - Truong, Aaron
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - Temporal trait of crashes has huge impact on road crash occurrence and a large proportion of research have considered different time periods to determine the causes and features of crash occurrence or frequency. Compared with other safety studies based on a single time interval, considerably less research has relied on the use of multiple time units, especially for the time intervals of less than one year. The research aims to fill the gap by investigating the temporal distribution of crash counts using multiple time spans including hour, weekday and month. To illustrate the most accurate results possible, both the Chi-square test and Cochran-Mantel-Haenzel tests were employed to explore the independence of various time units based on two-way and three-way contingency tables. Eight contingency table models were developed which can be classified into four groups including Complete Independence, Joint Independence, Conditional Independence and Homogeneous Association. Finally, a set of evaluation criteria were utilized for evaluation of the model performance. The results revealed the significant association existence in all time variables (hour, weekday, month) and the model with both main and all interactive effects of time variables provides best prediction performance. Also, the findings showed that Hour 18, weekdays 1, 6, 7 (Friday and Weekends), and month 8 (August) have the largest number of crash occurrences. It is suggested that both main and interactive effects of time variables should be included for model development, which otherwise might yield misleading information. It is anticipated that research results will benefit the safety professionals with better understanding of the temporal patterns of crashes with different time periods and allow the safety administrators to allocate the safety resources.<p />  <p>Language: en</p>
LA  - en
SN  - 1745-7300
UR  - http://dx.doi.org/10.1080/17457300.2021.1928231
ID  - ref1
ER  -