Showing 1 - 4 of 4 Research Library Publications
Posted: | M. von Davier, YS. Lee

Springer International Publishing; 2019

 

This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications. It brings together not only the current state of the art, but also the theoretical background and models developed for diagnostic classification.

Posted: | S. H. Felgoise, R. A. Feinberg, H. B. Stephens, P. Barkhaus, K. Boylan, J. Caress, Z. Simmons

Muscle Nerve, 58: 646-654

 

The Amyotrophic Lateral Sclerosis (ALS)‐Specific Quality of Life instrument and its revised version (ALSSQOL and ALSSQOL‐R) have strong psychometric properties, and have demonstrated research and clinical utility. This study aimed to develop a short form (ALSSQOL‐SF) suitable for limited clinic time and patient stamina.

Posted: | D. Franzen, M. Cuddy, J. S. Ilgen

Journal of Graduate Medical Education: June 2018, Vol. 10, No. 3, pp. 337-338

 

To create examinations with scores that accurately support their intended interpretation and use in a particular setting, examination writers must clearly define what the test is intended to measure (the construct). Writers must also pay careful attention to how content is sampled, how questions are constructed, and how questions perform in their unique testing contexts.1–3 This Rip Out provides guidance for test developers to ensure that scores from MCQ examinations fit their intended purpose.

Posted: | M. C. Edwards, A. Slagle, J. D. Rubright, R. J. Wirth

Qual Life Res 27, 1711–1720 (2018)

 

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.