| Sumario: | Measurement is an integral part of many disciplines, ranging from the social, healthcare/medical, to management sciences. The field of psychometrics has had a wide-ranging impact in the varied disciplines housed within psychology (e.g., clinical, developmental, etc.) as researchers and test developers aim to construct, refine, and modify their instruments. Given that test validation is a key component in furnishing evidence of validity, the intent of this nontechnical article is to reinforce (or serve as a reminder) for the applied audience the necessary efforts in optimizing the psychometric properties of their measurement tool. This article will be couched as a "lessons learned" document, primarily covering construct and criterion validity, but also, reliability estimation, and then finally, a comment about the confluence of null hypothesis significance testing, sample size and effect size and its relationship to psychometric testing.
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