Survey Datasets

How Effective Are Attitudinal Variables at Improving Travel Behavior Models? Evaluation Using an Overlapping Sample From an Attitude-Rich Survey and the 2017 National Household Travel Survey

A line of research has recently been launched on attitude imputation using machine learning (ML) functions trained on variables common to two survey datasets (Mokhtarian, 2024). It was discovered that using a handful of attitudinal marker variables (i.e., the one or two attitudinal items most strongly associated with each attitude) as common variables for imputation

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