Page 38 - tmp_Neat

In addition to estimating the coefficients, many studies have also computed the odds ratios.

When an independent variable xi increases by one unit, with all other factors remaining
constant, the odds increase by a factor exp ( i), which is called the odds ratio (OR), and it

ranges from zero to positive infinity. The OR indicates the relative amount by which the odds

of the outcome (crash occurring at an intersection rather than in mid-block) increase (OR>1)
or decrease (OR<1) when the value of the corresponding independent variable (e.g.

percentage of heavy vehicles) increases by one unit.

3.2.3 Random Parameter Logit (Mixed Logit Model)

A summary of existing studies on random parameter logit model is presented in Section

2.2.1.5 of Chapter Two. Random parameters, or mixed logit, were applied to allow the
possibility that the parameters may vary across observations (Washington et al., 2010). Some

researchers have chosen to use the random coefficient logit or probit model to allow for
heterogeneous effects and correlations in unobserved factors (Milton et al., 2008; Kim et al.,

2010; Anastasopoulos & Mannering, 2011; Tay, 2015). Random parameter models,

especially the random parameter logit or mixed logit models, have been increasingly used in
traffic safety studies to analyse both crash frequency and severity (Lord & Mannering, 2010;

Savolainen et al., 2011). To develop the mixed logit model, this study follows Milton et al.,

(2008) as follows:

(3.4)

where,

= is a linear function for determining the outcome (crash locations),

= a vector of estimated coefficients,

= a vector of explanatory variables,

= is an error term.

27