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Erschienen in:
2009 | OriginalPaper | Buchkapitel
2. A Guide to Implementing Quantitative Bias Analysis
verfasst von : Timothy L. Lash, Aliza K. Fink, Matthew P. Fox
Erschienen in: Applying Quantitative Bias Analysis to Epidemiologic Data
Verlag: Springer New York
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Abstract
Estimates of association from nonrandomized epidemiologic studies are susceptible to two types of error: random error and systematic error. Random error, or sampling error, is often called chance, and decreases toward zero as the sample size increases and the data are more efficiently distributed in the categories of the adjustment variables. The amount of random error in an estimate of association is measured by its precision. Systematic error, often called bias, does not decrease toward zero as the sample size increases or with more efficient distributions in the categories of the analytic variables. The amount of systematic error in an estimate of association is measured by its validity.