6533b854fe1ef96bd12afc6b

RESEARCH PRODUCT

Design Issues and Sample Size when Exposure Measurement is Inaccurate

G. Rippin

subject

Advanced and Specialized NursingOptimal designObservational errorComputer scienceEstimatorHealth InformaticsStatistical modelReliability engineeringReduction (complexity)Health Information ManagementSample size determinationReplication (statistics)StatisticsError detection and correction

description

AbstractMeasurement error often leads to biased estimates and incorrect tests in epidemiological studies. These problems can be corrected by design modifications which allow for refined statistical models, or in some situations by adjusted sample sizes to compensate a power reduction. The design options are mainly an additional replication or internal validation study. Sample size calculations for these designs are more complex, since usually there is no unique design solution to obtain a prespecified power. Thus, additionally to a power requirement, an optimal design should also fulfill the criteria of minimizing overall costs. In this review corresponding strategies and formulae are described and appraised.

https://doi.org/10.1055/s-0038-1634476