This paper shows how we can use a relatively new method to construct time-based homeless typologies that expand our ability to theorize and to make policy. Our key argument is that commonly created "time-aggregated" typologies lose potentially useful information by summing, averaging or otherwise summarizing events that occur over time. We suggest instead a "time-patterned" approach that captures events as they unfurl over time by measuring their timing, duration and sequencing. Comparing time-aggregated and time-patterned analyses of Kuhn and Culhane's prominent three-category typology, we find the time-patterned approach performs marginally better. We argue, however, that both analyses reveal problematic heterogeneity in the three groups and that the initial theorizing is not robust. These deficiencies suggest the utility of further analysis. Using the time-patterned results, we identify a four-pattern/ten-group typology that technically and substantively contrasts strongly with the prevailing three-category typology. We then imagine how structural factors and individual traits can combine to generate these observed homeless patterns, and conclude that either approach and either typology may be appropriate, depending on theorizing and the uses to which the findings are to be put
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