A Note On Generalized Ordered Outcome Models

Keywords

Generalized Ordered Logit; Ordered discrete outcome models; Ordinal discrete variables; Partial proportional odds model; Transportation safety; Unobserved heterogeneity

Abstract

While there is growing application of generalized ordered outcome model variants (widely known as Generalized Ordered Logit (GOL) model and Partial Proportional Odds Logit (PPO) model) in crash injury severity analysis, there are several aspects of these approaches that are not well documented in extant safety literature. The current research note presents the relationship between these two variants of generalized ordered outcome models and elaborates on model interpretation issues. While these variants arise from different mathematical approaches employed to enhance the traditional ordered outcome model, we establish that these are mathematically identical. We also discuss how one can facilitate estimation and interpretation while building on the ordered outcome model estimates - a useful process for practitioners considering upgrading their existing traditional ordered logit/probit injury severity models. Finally, the note presents the differences within GOL and PPO model frameworks, for accommodating the effect of unobserved heterogeneity, referred to as Mixed Generalized Ordered Logit (MGOL) and Mixed Partial Proportional Odds Logit (MPPO) models while also discussing the computational difficulties that may arise in estimating these models.

Publication Date

12-29-2015

Publication Title

Analytic Methods in Accident Research

Volume

8

Number of Pages

1-6

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.amar.2015.04.002

Socpus ID

84940477104 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84940477104

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