A typology of validity: content, face, convergent, discriminant, nomological and predictive validity

PurposeResearch serves to elucidate and tackle real-world issues (e.g. capitalizing opportunities and solving problems). Critical to research is the concept of validity, which gauges the extent to which research is adequate and appropriate in representing what it intends to measure and test. In this vein, this article aims to present a typology of validity to aid researchers in this endeavor.Design/methodology/approachEmploying a synthesis approach informed by the 3Es of expertise, experience, and exposure, this article maintains a sharp focus on delineating the concept of validity and presenting its typology.FindingsThis article emphasizes the importance of validity and explains how and when different types of validity can be established. First and foremost, content validity and face validity are prerequisites assessed before data collection, whereas convergent validity and discriminant validity come into play during the evaluation of the measurement model post-data collection, while nomological validity and predictive validity are crucial in the evaluation of the structural model following the evaluation of the measurement model. Additionally, content, face, convergent and discriminant validity contribute to construct validity as they pertain to concept(s), while nomological and predictive validity contribute to criterion validity as they relate to relationship(s). Last but not least, content and face validity are established by humans, thereby contributing to the assessment of substantive significance, whereas convergent, discriminant, nomological and predictive validity are established by statistics, thereby contributing to the assessment of statistical significance.Originality/valueThis article contributes to a deeper understanding of validity’s multifaceted nature in research, providing a practical guide for its application across various research stages.