Reliability of COVID-19 data: An evaluation and reflection.

Importance: The rapid proliferation of COVID-19 has left governments scrambling, and several data aggregators are now assisting in the reporting of county cases and deaths. The different variables affecting reporting (e.g.

Selecting the "Best" Factor Structure and Moving Measurement Validation Forward: An Illustration.

Despite the broad literature base on factor analysis best practices, research seeking to evaluate a measure's psychometric properties frequently fails to consider or follow these recommendations. This leads to incorrect factor structures, numerous and often overly complex competing factor models and, perhaps most harmful, biased model results. Our goal is to demonstrate a practical and actionable process for factor analysis through (a) an overview of six statistical and psychometric issues and approaches to be aware of, investigate, and report when engaging in factor structure validation, along with a flowchart for recommended procedures to understand latent factor structures; (b) demonstrating these issues to provide a summary of the updated Posttraumatic Stress Disorder Checklist (PCL-5) factor models and a rationale for validation; and (c) conducting a comprehensive statistical and psychometric validation of the PCL-5 factor structure to demonstrate all the issues we described earlier.

Development and validation of PediaTrac™: A web-based tool to track developing infants.

Objective: PediaTrac™, a 363-item web-based tool to track infant development, administered in modules of ∼40-items per sampling period, newborn (NB), 2--, 4--, 6--, 9-- and 12--months was validated. Caregivers answered demographic, medical, and environmental questions, and questions covering the sensorimotor, feeding/eating, sleep, speech/language, cognition, social-emotional, and attachment domains.

Methods: Expert Panel Reviews and Cognitive Interviews (CI) were conducted to validate the item bank.

Learning curve analyses in neurodevelopmental disorders: are children with autism spectrum disorder truly visual learners?

Visual and auditory verbal learning using a selective reminding format was studied in a mixed clinical sample of children with autism spectrum disorder (ASD) (n = 42), attention-deficit hyperactivity disorder (n = 83), velocardiofacial syndrome (n = 17) and neurotypicals (n = 38) using the Test of Memory and Learning to (1) more thoroughly characterize and examine the integrity of learning and memory processes, (2) to better understand the mechanisms of learning impairment, and (3) to inform instructional practices in ASD. Contrary to expectations, children with ASD demonstrated a relative weakness in the rate of acquisition of visual in contrast to verbal learning compared to neurotypicals. They also showed a complex pattern of consolidation.

Self-report methodology is insufficient for improving the assessment and classification of Axis II personality disorders.

Current approaches to the assessment and classification of personality disorders (PDs) rely almost exclusively on self-report methodology. In this paper, we document the many difficulties with self-reports, including limitations in their accuracy, the confounding effect of mood state, and problems with the selection and retention of factors in factor analytic approaches to self-report questionnaires. We also discuss the role of implicit processes in self-reports, with special attention directed to the phenomenon of priming and its effect on outcome.

A Comparative Investigation of Rotation Criteria Within Exploratory Factor Analysis.

Exploratory factor analysis (EFA) is a commonly used statistical technique for examining the relationships between variables (e.g., items) and the factors (e.

Comparing factor analytic models of the DSM-IV personality disorders.

There is little agreement about the latent factor structure of the Diagnostic and Statistical Manual of Mental Disorders (DSM) personality disorders (PDs). Factor analytic studies over the past 2 decades have yielded different results, in part reflecting differences in factor analytic technique, the measure used to assess the PDs, and the changing DSM criteria. In this study, we explore the latent factor structure of the DSM (4th ed.

Assessing interpersonal fusion: reliability and validity of a new DSI fusion with others subscale.

The Differentiation of Self Inventory (DSI) is a multidimensional measure of differentiation consisting of four subscales focusing on adults (ages 25+), and their significant relationships, including current relationships with family of origin. Although the DSI full scale and three of its subscales are theoretically and psychometrically sound, the Fusion with Others (FO) subscale is lacking. Therefore, responses of 225 adults were used to revise the FO subscale.