Investigating Contextual Variability in Mode Choice in Chicago Using a Hierarchical Mixed Logit Model

Urban Studies ◽  
2010 ◽  
Vol 47 (11) ◽  
pp. 2445-2459 ◽  
Author(s):  
Liang Long ◽  
Jie Lin ◽  
Kimon Proussaloglou
Keyword(s):  
Logit Model ◽  
Mode Choice ◽  
Mixed Logit ◽  
Mixed Logit Model ◽  
Contextual Variability

Modeling head-on crash severity on NCDOT freeways: a mixed logit model approach

2019 ◽  
Vol 46 (4) ◽  
pp. 322-328 ◽  
Author(s):  
Pengfei Liu ◽  
Wei (David) Fan
Keyword(s):  
Logit Model ◽  
Injury Severity ◽  
Safety Information ◽  
Mixed Logit ◽  
Weather Condition ◽  
Mixed Logit Model ◽  
Young Drivers ◽  
Adverse Weather Condition ◽  
Adverse Weather ◽  
Model Approach

This study employs a mixed logit model approach to evaluate contributing factors that significantly affect the severity of head-on crashes. The head-on crash data are collected from Highway Safety Information System (HSIS) from 2005 to 2013 in North Carolina. The effects that vehicle, driver, roadway, and environmental characteristics have on the injury severity of head-on crashes are examined. The results of this research demonstrate that adverse weather, young drivers, rural roadways, and pickups are found to be better modeled as random-parameters at specific injury severity levels, while others should remain fixed. Also, the model results indicate that driving under the influence of alcohol or drugs, grade or curve roadway configuration, old drivers, high speed limit, motorcycles will increase the injury severity of head-on crashes. Adverse weather condition, two-way divided road, traffic control, young drivers, and pickups will decrease the injury severity of head-on crashes.

Quality and Consumer Choice in Healthcare: Evidence from Kidney Transplantation

2006 ◽  
Vol 5 (1) ◽  
Author(s):  
David H Howard
Keyword(s):  
Kidney Transplantation ◽  
Consumer Choice ◽  
Logit Model ◽  
Mixed Logit ◽  
Mixed Logit Model ◽  
Hospital Level ◽  
Standard Deviation Increase ◽  
Policy Debates ◽  
Medicare Patients ◽  
Insured Patients

AbstractMost studies of competition in health care focus on prices and costs, but concerns about quality play a central role in policy debates. If demand is inelastic to quality, then competition may reduce patient welfare. This study uses a dataset of patient registrations for kidney transplantation in conjunction with a mixed logit model to gauge consumers’ responsiveness to quality when choosing hospitals. Results indicate that at the hospital level, a one-standard deviation increase in the graft-failure rate is associated with a 6% decline in patient registrations. Privately-insured patients are more responsive to quality than Medicare patients, suggesting that insurers consider quality when contracting with providers.

Sign in / Sign up

Export Citation Format

Share Document