On Accommodating Spatial Interactions in a Generalized Heterogeneous Data Model (GHDM) of Mixed Types of Dependent Variables

Multi-dimensional dependent outcome models are of interest in several fields, including land-use and transportation, biology, finance, and econometrics, just to name a few. The primary motivation for modeling dependent outcomes jointly is that there may be common underlying unobserved factors (attitudes, values, and lifestyle factors) of decision-makers that impact multiple dependent outcomes simultaneously. Even as there has been increasing emphasis on mixed data outcome modeling, there also has been a growing interest in accommodating spatial (and social) dependency effects among decision-makers in mixed data modeling. This is because spatial/social interactions can be exploited by decision-makers to achieve desired system end-states. In the current project, the use of important insight that the analyst can generate spatial dependence across multiple and mixed outcomes by specifying spatial dependence in the “soft” psychological construct (latent) variables underlying the many outcomes.

• Record URL:
  http://ctr.utexas.edu/research/d-stop/research/projects/

Language

• English

Project

• Status: Completed
• Funding: $20000
• Contract Numbers:

  DTRT13-G-UTC58

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Project Managers:

  Bhat, Chandra

• Performing Organizations:

  Data-Supported Transportation Operations and Planning Center

  University of Texas at Austin
  Austin, TX  United States  78701
• Principal Investigators:

  Bhat, Chandra

• Start Date: 20150101
• Expected Completion Date: 20151231
• Actual Completion Date: 20151231
• Source Data: 120

Subject/Index Terms

• TRT Terms: Attitudes; Data analysis; Decision making; Heterogeneity; Land use models; Social impacts; Spatial analysis
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Research;

Filing Info

• Accession Number: 01580145
• Record Type: Research project
• Source Agency: Data-Supported Transportation Operations and Planning Center
• Contract Numbers: DTRT13-G-UTC58
• Files: UTC, RiP
• Created Date: Oct 29 2015 12:30PM