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We investigate the nature of measurement error in time-use data. Analysis of “stylized” recall questionnaire estimates and diary-based estimates of housework time from the same respondents of a British survey gives evidence of systematic biases in the stylized estimates and large random errors in both types of estimates. We examine the effect of these measurement problems on three common types of statistical analyses in which the time-use variable is used as: (1) adependent variable, (2) an explanatory variable, and (3) a basis for cross-tabulations. We develop methods to correct the biases induced by these measurement errors.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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