Below, I summarize the key areas of my ongoing research.
Replication x Psychometrics
My program of research has been focused on exploring psychometric issues from a meta-science perspective. Specifically, I have been interested in the replicability of psychometric analyses (i.e., psychometric replication). Recent work in this area includes the development of a taxonomy for assessing research and reporting practices (Manapat et al., 2024) as well as a simulation study that examines the replicability of exploratory factor analyses (Manapat et al., in press). I am currently working on extending the simulation work to confirmatory factor analysis and the structural model.
Non-Normality
Distributional assumptions for latent constructs can affect the validity of psychometric work. In practice, latent constructs are often assumed to follow a normal distribution. However, there are situations where this assumption is unreasonable (e.g., constructs of a clinical nature - tend to be low for most people, medium for some, and high for few). Recent work includes an examination of the types and degrees of non-normality most detrimental to parameter recovery for the 2-parameter logistic and graded response models (Manapat & Edwards, 2022).
Applied Collaborations
As a graduate research associate for Dr. Dave MacKinnon in the Research in Prevention Laboratory at Arizona State University (ASU), I led a project to assess the dimensionality of the Brief Self-Control Scale using both factor analysis and item response theory approaches (Manapat et al., 2021). More recently, I collaborated with Dr. Lani Shiota and the SPLAT Lab at ASU. The project involved factor analyzing the Brief COPE scale, a measure that assesses coping strategies, and its association with COVID-specific health behaviors (Langley et al., 2023).