Experiment-Wise Type I Error Control: A Focus on 2 × 2 Designs
Andrew V. Frane
Abstract
Factorial designs are common in psychology research. But they are nearly always used without control of the experiment-wise Type I error rate (EWER), perhaps because of a lack of awareness about viable procedures for that purpose and perhaps also because of a lack of appreciation for the problem of Type I error inflation. In this article, key concepts relating to Type I error inflation are discussed, with emphasis on the 2 × 2 factorial design. Simulations are used to evaluate various approaches in that context. I show that conventional approaches often do not control the EWER. Alternative approaches are recommended that reliably control the EWER and are simple to implement.
Topics & Concepts
Type I and type II errorsComputer scienceFocus (optics)Control (management)Context (archaeology)Factorial experimentError detection and correctionWord error rateType (biology)Inflation (cosmology)EconometricsAlgorithmStatisticsMathematicsMachine learningArtificial intelligencePaleontologyPhysicsOpticsEcologyTheoretical physicsBiologyStatistical Methods in Clinical TrialsOptimal Experimental Design MethodsAdvanced Causal Inference Techniques