Assessing the Relationship Between Sample Representativeness and External Validity in Statistical Research Studies

Posted: Dec 02, 2021

• Grace Wilson
• Henry Baker
• Abigail Carter

Abstract

This research investigates the complex relationship between sample representativeness and external validity in statistical research studies, proposing a novel multidimensional framework that challenges conventional assumptions about generalizability. While traditional statistical methodology emphasizes random sampling as the primary mechanism for ensuring external validity, our study demonstrates through extensive simulation and empirical analysis that representativeness operates through multiple distinct pathways that interact in non-linear ways. We introduce the concept of 'representational congruence' as a more comprehensive measure than traditional representativeness metrics, accounting for both structural similarity and functional equivalence between sample and target populations. Our methodology combines computational simulations across diverse population structures with meta-analysis of 127 published studies spanning social sciences, medical research, and public policy. The results reveal that conventional random sampling approaches achieve only moderate external validity (mean correlation r = 0.42) even under ideal conditions, while our proposed multidimensional framework improves predictive accuracy by 31-47