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Psychometrics and statistics: two pillars of neuropsychological practice

Psychometrics and statistics are two of the foundational elements of the measurement tools used in neuropsychological practice. It is imperative that clinical neuropsychologists have a firm grasp on measurement properties and statistical approaches used in the development and validation of assessment methods they use and that they keep abreast of the latest advances in these areas. The primary objectives of this special issue on ‘New Developments and Common Misperceptions about Psychometrics and Statistics in Neuropsychological Practice’ were to: (1) highlight new statistical and psychometric advances that are relevant to the practice of clinical neuropsychology, and (2) draw attention to commonly held misconceptions about clinically relevant psychometric and statistical principles. Contributing authors were encouraged to submit work addressing such topics as the clinical impact of different approaches to norm development and the utility of Bayesian statistics for diagnostic decision-making, as well as papers introducing new or emerging psychometric or statistical approaches, concepts, and/or tools that could be used in clinical practice. This special issue is divided into two sections, Conceptual Articles and Applied Studies. The opening article of the conceptual section by Gelman and Geurts (2017) reminds us of the importance of replication in science and outlines five major challenges specific to evaluating the strength of experimental evidence within clinical neuropsychology. Gelman and Geurts discuss potential solutions and urge neuropsychologists to ensure our own methods sections are detailed enough to allow replication and critical review of findings. The following article by Lange and Lippa (2017) offers another important reminder about the need to consider base rates and all diagnostic accuracy metrics, including positive and negative predictive power, when evaluating the clinical utility of a test or measure. Lange and Lippa review the critical elements of test operating characteristics and present guidelines for evaluating and selecting cut-off values. They also recommend qualitative descriptors for these values that will be useful to all neuropsychologists. In a thought-provoking article, Erdodi and Lichtenstein (2017) highlight the conundrum facing many neuropsychologists who attempt to utilize embedded validity indicators. The ‘invalid-before-impaired’ paradox refers to the situation when scores on embedded validity measures are deemed invalid as they are nearing the threshold of impairment or even before reaching this threshold. Erdodi and Lichtenstein walk through a methodological exercise to illustrate this dilemma and engage in a discussion of the interpretative implications and potential solutions. In the final article of the conceptual section, Brown, Thomas, and Patt (2017) discuss measure precision in neuropsychological assessment and advocate for the use of parametric measurement models to estimate latent neurobehavioral processes that are then linked to responses on neuropsychological tests. With the increasing availability of statistical computer programs that can implement sophisticated computational analyses, Brown and colleagues argue that now is the time for neuropsychologists to apply complex psychometric models to neuropsychological test data with the goal of achieving more precise and nuanced interpretation of individual differences in neuropsychological functioning. The Applied Studies section consists of a compilation of articles addressing topics ranging from new approaches to the utilization of neuropsychological test data to considerations in