In linear regression problems with many predictors, penalized regression techniques are
often used to guard against overfitting and to select variables relevant for predicting an …

Abstract Commentary in Widaman and Revelle argued that sum scoring is justified as long
as unidimensionality holds because sum score reliability is defined. My response begins …

Methodological innovations have allowed researchers to consider increasingly
sophisticated statistical models that are better in line with the complexities of real-world …

To reasonably implement the operational reliability analysis and describe the importance of
the influencing parameters for the operation status, a framework for operational reliability …

Correct detection of measurement bias could help researchers revise models or refine
psychological scales. Measurement bias detection can be viewed as a variable-selection …

Regularized continuous time structural equation models are proposed to address two recent
challenges in longitudinal research: Unequally spaced measurement occasions and high …

Predictive modeling is becoming more popular in psychological science. Machine learning
techniques have been used to develop prediction rules based on items of psychological …

Exploratory factor analysis (EFA) is an important tool when the measurement structure of
psychological constructs is uncertain. Typically, factor rotation is applied to obtain …

An important step in scale development and assessment is to evaluate differential item
functioning (DIF) across segments of the population. Recent approaches use lasso …

With small to modest sample sizes and complex models, maximum likelihood (ML)
estimation of confirmatory factor analysis (CFA) models can show serious estimation …