A new study from the American Transportation Research Institute (ATRI) found that active memberships in state and national associations are safer than former members and individuals who have never been members.
“It has always been anecdotally assumed that association membership supports safety through a variety of association services and resources, but the necessary industry safety data and methodology had never before been assessed,” an ATRI news release stated.
“This new empirical research processed public safety data from the Motor Carrier Management Information System (MCMIS) through a series of statistical tools to confirm the relationship between association membership and safety performance.”
The research that was conducted looked at and compared motor carrier MCMIS crash and violation data for fleets that currently held memberships, former members, and people who were never members.
Carrier status data came from a geographically representative sample of state trucking associations as well as from the American Trucking Associations.
The Welch’s Two-Sample T-Test outputs have confirmed that among the three carrier groups (current members, former members, and never members), current members have fewer overall crashes and violations than former members.
Additionally, ATRI found that former members also had fewer crashes and violations than never members. The results of the T-tests were significant at the 95% or 99% confidence levels, indicating a high level of confidence in the observed differences.
It is important to note that the Welch’s T-test is an adapted version of the Student’s T-test that can be more reliable when the variances of the two independent samples cannot be assumed to be equal. The Welch’s T-test is more robust than the Student’s T-test and maintains type I error rates close to nominal for unequal variances and unequal sample sizes under normality.
Furthermore, the power of Welch’s T-test comes close to that of Student’s T-test, even when the population variances are equal and sample sizes are balanced. The Welch’s T-test can also be generalized to more than two samples, which is more robust than one-way analysis of variance.
It is also worth noting that the interpretation of the T-test results can be confusing, especially when dealing with small datasets. The T-test is testing two competing hypotheses: H0 (null hypothesis) and Ha (alternative hypothesis).
The null hypothesis assumes that there is no difference between the true averages of the two groups, while the alternative hypothesis assumes that there is a significant difference between the averages of the two groups. The p-value is used to determine whether the null hypothesis can be rejected or not.
Finally, it is important to mention that due to the rarity of fatal truck crashes among all carriers, this specific crash type was not significant for either state or national membership. This suggests that the differences in fatal truck crashes among the carrier groups may not be statistically significant.
“All safety stakeholders in the trucking industry are looking for strategies and solutions for improving large-truck safety,” said Dr. Brenda Lantz, associate director of the Upper Great Plains Transportation Institute. “This new ATRI research confirms that association membership is another important and proven safety tool for trucking companies.”
