Pure mathematics

Inference

Mathematics

Operations research

Statistics

Goodness of fit

Heuristic

Econometrics

Artificial intelligence

Data science

Computer science

Field (mathematics)

Model validation

Journal of Choice Modelling

An examination of model validation practices in the peer-reviewed transportation literature published between 2014 and 2018 reveals that 92% of studies reported goodness-of-fit statistics, and 64.6% reported some sort of policy-relevant inference analysis. However, only 18.1% reported validation performance measures, out of which 78% (14.2% of all studies) consisted of internal validation and 22% (4% of all studies) consisted of external validation. The proposition put forward in this paper is that the reliance on goodness-of-fit measures rather than validation performance is unwise, especially given the dependence of the transportation research field on observational (non-experimental) studies. Model validation should be a non-negotiable part of presenting a model for peer-review in academic journals. For that purpose, we propose a simple heuristic to select validation methods given the resources available to the researcher.

The overreliance on statistical goodness-of-fit and under-reliance on model validation in discrete choice models: A review of validation practices in the transportation academic literature