Drawing Statistical Inferences from Historical Census Data

Michael Davern, Steven Ruggles, Tami Swenson & J. Michael Oakes
Virtually all quantitative microdata used by social scientists derive from samples that incorporate clustering, stratification, and weighting adjustments (Kish 1992, 1965). Such data can yield standard error estimates that differ dramatically from a simple random sample of the same size. Researchers using historical U.S. census microdata, however, usually apply methods designed for simple random samples. The resulting p-values and confidence intervals could be inaccurate and could lead to erroneous research conclusions. Because U.S. census microdata...
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