This article briefly reviews the aspects of validity that researchers should consider when using surveys. It then focuses on factor analysis, a statistical method that can be used to collect an important type of validity evidence.
The widespread move to computerized test delivery has led to the development of new approaches to evaluating how examinees use testing time and to new metrics designed to provide evidence about the extent to which time limits impact performance. Much of the existing research is based on these types of observational metrics; relatively few studies use randomized experiments to evaluate the impact time limits on scores. Of those studies that do report on randomized experiments, none directly compare the experimental results to evidence from observational metrics to evaluate the extent to which these metrics are able to sensitively identify conditions in which time constraints actually impact scores. The present study provides such evidence based on data from a medical licensing examination.
The research presented in this article combines mathematical derivations and empirical results to investigate effects of the nonparametric anchoring vignette approach proposed by King, Murray, Salomon, and Tandon on the reliability and validity of rating data. The anchoring vignette approach aims to correct rating data for response styles to improve comparability across individuals and groups.
The US Food and Drug Administration (FDA), as part of its regulatory mission, is charged with determining whether a clinical outcome assessment (COA) is “fit for purpose” when used in clinical trials to support drug approval and product labeling. This paper provides a review (and some commentary) on the current state of affairs in COA development/evaluation/use with a focus on one aspect: How do you know you are measuring the right thing? In the psychometric literature, this concept is referred to broadly as validity and has itself evolved over many years of research and application.