Quantifying errors without random sampling.

ABSTRACT:

Background

All quantifications of mortality, morbidity, and other health measures involve numerous sources of error. The routine quantification of random sampling error makes it easy to forget that other sources of error can and should be quantified. When a quantification does not involve sampling, error is almost never quantified and results are often reported in ways that dramatically overstate their precision.

Discussion

We argue that the precision implicit in typical reporting is problematic and sketch methods for quantifying the various sources of error, building up from simple examples that can be solved analytically to more complex cases. There are straightforward ways to partially quantify the uncertainty surrounding a parameter that is not characterized by random sa

SUBMITTER: Phillips CV 

PROVIDER: S-EPMC166164 | biostudies-literature | 2003 Jun

REPOSITORIES: biostudies-literature