Joint analysis of dispersed count-time data using a bivariate latent factor model.

ABSTRACT: In this study, we explore parameter estimation for a joint count-time data model with a two-factor latent trait structure, representing accuracy and speed. Each count-time variable pair corresponds to a specific item on a measurement instrument, where each item consists of a fixed number of tasks. The count variable represents the number of successfully completed tasks and is modeled using a Beta-binomial distribution to account for potential over-dispersion. The time variable, representing the duration needed to complete the tasks, is modeled using a normal distribution on a logarithmic scale. To characterize the model structure, we derive marginal moments that inform a set of method-of-moments (MOM) estimators, which serve as initial values for maximum likelihood estimation (MLE) via the

SUBMITTER: Potgieter CJ 

PROVIDER: S-EPMC12784336 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature