Related Experiment Video
Updated: Feb 14, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Multivariate dynamic Tobit models with lagged observed dependent variables: An effectiveness analysis of highway
Chunjiao Dong1, Kun Xie2, Jin Zeng3
1Center for Transportation Research, Tickle College of Engineering, University of Tennessee, 600 Henley Street, Knoxville, TN 37996, USA; School of Traffic & Transportation, Beijing Jiaotong University, Beijing 100044, China.
Abstract:
Highway safety laws aim to influence driver behaviors so as to reduce the frequency and severity of crashes, and their outcomes. For one specific highway safety law, it would have different effects on the crashes across severities. Understanding such effects can help policy makers upgrade current laws and hence improve traffic safety. To investigate the effects of highway safety laws on crashes across severities, multivariate models are needed to account for the interdependency issues in crash counts across severities. Based on the characteristics of the dependent variables, multivariate dynamic Tobit (MVDT) models are proposed to analyze crash counts that are aggregated at the state level. Lagged observed dependent variables are incorporated into the MVDT models to account for potential temporal correlation issues in crash data. The state highway safety law related factors are used as the explanatory variables and socio-demographic and traffic factors are used as the control variables. Three models, a MVDT model with lagged observed dependent variables, a MVDT model with unobserved random variables, and a multivariate static Tobit (MVST) model are developed and compared. The results show that among the investigated models, the MVDT models with lagged observed dependent variables have the best goodness-of-fit. The findings indicate that, compared to the MVST, the MVDT models have better explanatory power and prediction accuracy. The MVDT model with lagged observed variables can better handle the stochasticity and dependency in the temporal evolution of the crash counts and the estimated values from the model are closer to the observed values. The results show that more lives could be saved if law enforcement agencies can make a sustained effort to educate the public about the importance of motorcyclists wearing helmets. Motor vehicle crash-related deaths, injuries, and property damages could be reduced if states enact laws for stricter text messaging rules, higher speeding fines, older licensing age, and stronger graduated licensing provisions. Injury and PDO crashes would be significantly reduced with stricter laws prohibiting the use of hand-held communication devices and higher fines for drunk driving.
Related Concept Videos
The Integrated Rate Law: The Dependence of Concentration on Time
Variability: Analysis
The range is a simple measure of variability, indicating the difference between the highest and...
Lagging Strand Synthesis
There are several major differences between synthesis of the leading strand and synthesis of the lagging strand. 1) Leading strand synthesis happens in the direction of replication fork opening, whereas lagging strand synthesis happens in the...
Lagging Strand Synthesis
Scientific Laws and Theories
Concentration and Rate Law
For example, in a generic reaction aA + bB ⟶ products, where a and b are stoichiometric coefficients, the rate law can be written as:

