This report provides a summary of analyses using data of long distance tours by each household from an 8-week California Household Travel Survey travel log. The first analysis, uses Structural Equations Models (SEM) and a simpler variant called Path Analysis on three censored variables (tour miles by air, miles driving, and miles by public transportation) and two categorical variables (main trip tour purpose) and number of overnight stays. The second analysis, uses Latent Class Cluster Analysis (LCCA) to identify five distinct, informative patterns of long-distance travel. This analysis shows that long-distance tours for vacation, business travel, medical, and shopping are substantially distinct in terms of their travel characteristics and correspond to different combinations of other activities in the tour and they are done by different types of households. The methods used here to identify the typology of long distance travel can be easily expanded to include a variety of other explanatory variables of this type of behavior in more focused data collection settings
