Do lower income areas have more pedestrian casualties?

Accident Analysis and Prevention

Volumn 59, Issue , 2013, Pages 337-345

  Noland, Robert B ^a   Klein, Nicholas J ^a   Tulach, Nicholas K ^a  

^a The State University of New Jersey   (United States)

Author keywords

Bayesian analysis; Car ownership; Deprivation; Low income; Negative binomial models; Pedestrians; Road safety

Indexed keywords

BAYESIAN ANALYSIS; CAR OWNERSHIP; DEPRIVATION; LOW INCOMES; NEGATIVE BINOMIAL MODELS; PEDESTRIANS; ROAD SAFETY;

BAYESIAN NETWORKS; MONTE CARLO METHODS; ROADS AND STREETS; VEHICLES;

PEDESTRIAN SAFETY;

ARTICLE; BAYES THEOREM; CAR; CAR OWNERSHIP; DEPRIVATION; HUMAN; INJURY; LOWEST INCOME GROUP; MONTE CARLO METHOD; MORTALITY; NEGATIVE BINOMIAL MODELS; PEDESTRIANS; POVERTY; PROBABILITY; ROAD SAFETY; STATISTICAL MODEL; STATISTICS; TRAFFIC ACCIDENT; UNITED STATES; WALKING;

BAYESIAN ANALYSIS; CAR OWNERSHIP; DEPRIVATION; LOW INCOME; NEGATIVE BINOMIAL MODELS; PEDESTRIANS; ROAD SAFETY;

ACCIDENTS, TRAFFIC; AUTOMOBILES; BAYES THEOREM; HUMANS; LIKELIHOOD FUNCTIONS; MARKOV CHAINS; MODELS, STATISTICAL; MONTE CARLO METHOD; NEW JERSEY; POVERTY AREAS; WALKING;

EID: 84880298305     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2013.06.009     Document Type: Article

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