Lawrence Nitz

Personal and behavioral predictors of automobile crash and injury severity

The purpose of this paper is to develop a statistical model explaining the relationships between certain driver characteristics and behaviors, crash severity, and injury severity. Applying techniques of categorical data analysis to comprehensive data on crashes in Hawaii during 1990, we build a structural model relating driver characteristics and behaviors to type of crash and injury severity. The structural model helps to clarify the role of driver characteristics and behaviors in the causal sequence leading to more severe injuries. From the model we estimate the effects of various factors in terms of odds multipliers--that is, how much does each factor increase or decrease the odds of more severe crash types and injuries. We found that driver behaviors of alcohol or drug use and lack of seat belt use greatly increase the odds of more severe crashes and injuries. Driver errors are found to have a small effect, while personal characteristics of age and sex are generally insignificant. We conclude with a discussion of our modeling approach and of the implications of our findings for appropriate traffic safety interventions and future research.

Spatial analysis of Honolulu motor vehicle crashes: II. Zonal generators

The spatial relationship between activities which generate trips and motor vehicle accidents is examined and applied to the City and County of Honolulu for 1990. A method is described for examining spatial variations in motor vehicle accidents, aggregated into small geographical areas. A spatial lag model is developed which examines the zonal relationship of motor vehicle accidents to population, employment and road characteristics. The resulting model is tested for each hour of the day, weekdays and weekends separately. The predictors of accidents fluctuate according to different trip generating activities and change considerably over the day. The method can generate expected accidents, allowing for an identification of areas which have higher than expected levels. It is argued that this method focuses attention on characteristics of neighborhoods and areas, and not just on the road system.

Without cause or effect: Reconsidering welfare migration as a policy problem

Theory: Stories of welfare migration are often statistical narratives of economic rationality that portray welfare migrants as engaging in economically rational but illegitimate behavior. Three waves of scholarly studies of welfare migration can be delineated as reinforcing these stories with second-wave studies in particular providing evidence of welfare migration. Yet, it is questionable that: (1) state welfare benefits vary enough to induce welfare migration; (2) high levels of migration actually occur; and (3) the migration patterns of poor families ought to be narrated as economically rational behavior directed toward the maximization of welfare benefits. Hypotheses: Variation in the real value of welfare benefits is small. Welfare migration is an infrequent occurrence making for a small proportion of the total welfare budget. Better explanations narrate the migration patterns of poor families in terms other than those narrowly focused on welfare benefits. Methods: Data on welfare benefits and per capita income is used to assess the real value of welfare benefits. Data from the Public Use Microdata Set 5% sample of the United States Census is used to track the migration routes of poor single mothers with children. Results: Combined maximum benefits from Aid to Families with Dependent Children and Food Stamps are found to vary across the states only slightly more than per capita income. Approximately 90% of poor single mothers with children are not likely to move out-of-state over a five year period. Poor single mothers with children are not more likely to move to states with higher benefits. Narratives that account for alternative reasons, including increased safety, improved housing, better economic opportunities, and family ties, should be explored as explanations of the migration patterns of poor single mothers with children.

DAILY FLUCTUATIONS IN HONOLULU MOTOR VEHICLE ACCIDENTS

Changes in daily motor vehicle accidents during 1990 are examined for the City and County of Honolulu. Adjusting for changed reporting criteria, daily accidents fluctuate according to an interaction between traffic volume, weekday travel patterns, holidays and weather. Fridays, particularly, and Saturdays have more daily accidents. Minor holidays generate more daily accidents, but major holidays generate fewer daily accidents, primarily because of lower traffic volume. Rainfall increases the risk of accidents substantially. The interaction between afternoons and rainfall is particularly dangerous. Unemployment also appears to reduce daily accidents.

PREDICTORS OF SAFETY BELT USE AMONG CRASH-INVOLVED DRIVERS AND FRONT SEAT PASSENGERS: ADJUSTING FOR OVER-REPORTING

Police-reported crash data are rarely used to investigate safety belt use and its predictors, even though these data have a number of advantages over data collected in roadside surveys. It has been widely recognized that motorists tend to over-report their safety belt use to police when mandatory belt use becomes law. In this paper, we use a logistic regression model that allows for misclassification errors in outcome variable to examine predictors of safety belt use among crash-involved drivers and front seat passengers. Our analysis shows significant associations between occupant characteristics, driving circumstances, and safety belt use. Alcohol involvement has the strongest negative association with safety belt use, but this association would be considerably underestimated without adjusting for the over-reporting of safety belt use in police-reported crash data. The adjusted belt use rate among front seat occupants with at least nonincapacitating injuries is about 81%, compared to 90% in police-reported crash data.

Drivers at Fault: Influences of Age, Sex, and Vehicle Type

Using log-linear modeling techniques, the probability of fault among collision-involved drivers in Hawaii is related to three categorical variables: age, sex, and vehicle type. Very young and very old drivers face up to three times the risk of being at fault compared to middle-aged drivers. Substantial gender effects also occur at both ends of the age distribution. Pickup truck drivers have higher odds of being at fault than automobile drivers, while van drivers have lower odds. An ‘‘odds multiplier’’ computation combines the effects of the variables to permit comparison of the relative odds of fault between various categories of drivers. The implications of these findings are reviewed in terms of policy responses toward these high-risk combinations.

Patterns of motor vehicle crash involvement by driver age and sex in Hawaii

The purpose of this paper is to develop a statistical description of patterns of motor-vehicle crash types among drivers of different age and sex in order to identify underlying differences in behavior and ability. Using techniques of categorical data analysis and comprehensive data on crashes in Hawaii during 1991 and 1992, we relate crash type (e.g., sideswiper, sideswiped, rearender, rearended, etc.) to driver age and sex categories. We also examine interactions between driver age and sex, crash type, and vehicle type. By fitting a loglinear model, we find that different crash types are associated with different driver groups in a way that suggests systematic differences in driver behavior and ability. In particular, young drivers have much greater frequency of rollovers and of being the rearender or headoner, whereas older drivers have much higher frequency of being rearended, sideswiped, or broadsided. The most notable effect of vehicle type is the much higher frequency of rollover for pick-up trucks, a vehicle much more frequently driven by young male drivers. We conclude with a discussion of the implications of our findings for appropriate interventions and future research.

Moped safety in Honolulu, Hawaii

Between 1977 and 1990, mopeds in the city and county of Honolulu have more than tripled in number. There has also been a significant increase in the number of collisions involving mopeds. Using GIS tools and police crash reports for 1990, we describe the spatial and temporal patterns of moped collisions, identify the major causes and circumstances of these collisions, and identify the characteristics of moped riders involved in collisions. Our analysis demonstrates a spatial concentration around the University of Hawaii and tourist destinations. We compare resident and nonresident involvement in moped collisions. Based on these results, we provide several suggestions for improving moped safety among both residents and visitors.

The effects of divisibility of payoff on confederative behavior

In a recent study, Phillips and Nitz (1968) focused on the social contact process as a significant aspect of confederative behavior. The social contact process discussed occurs during a transitory phase of group formation when the potential group members move from an independent, noninteracting state into an interdependent state of interaction. The relative frequencies of social contacts were used to test hypotheses about coalition formation.