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Existing literature on people experiencing homelessness (PEH) draws on non-representative samples from service providers, populations with comorbidities, or areas with disproportionately high sheltered homelessness, leading to bias. Nearly a third of PEH in the US and over half of unsheltered PEH live in California. We designed a rigorous state-representative survey of PEH to investigate the antecedents of homelessness, understand health, and inform policy solutions. The multistage design randomized at three levels: county, venue, and individual. Stratifying the state into eight regions, we sampled one county per region to reflect statewide demographics. Within counties, sampled venues matched the expected proportion of sheltered and unsheltered residents. Within venues, interviewers randomly sampled individuals. We adjusted for nonresponse and incorporated poststratification to benchmarks. In parallel, respondent-driven sampling reached subpopulations through social networks who may otherwise have been under-sampled. Our community-engaged study yielded 3200 quantitative surveys. We purposively sampled 365 participants for qualitative interviews. Demographic estimates match those found in the PIT with the added strength of statistical inference. This is the first large representative study of PEH, beyond a single county, to draw inference on a large population that did not depend on service utilization. Our methods may inform future efforts to understand homelessness.
Wesson et al. (Wed,) studied this question.