Latent Interaction Modeling With Planned Missing Data Designs

• In Event: Marriott Roundtable Session 29
  In Roundtable Session: Missing Data Across Statistical Models

Abstract

Planned missing data (PMD) designs allow researchers to collect additional data under time constraints, which likely occur in educational research settings. The imposed missing data patterns, however, can hamper the efficiency of statistical models that are of interest to substantive researchers. Typically, PMD designs result in a modest power deficiency; however, this tenet has not been extended to latent interaction models. Such models are of increasing importance as researchers investigate moderated relationships involving continuous latent variables. Monte Carlo simulations are used to assess the efficacy of various latent interaction estimation methods under PMD designs.

Authors

• Jayden Nord, University of Nebraska - Lincoln

• James A. Bovaird, University of Nebraska - Lincoln

• Matthew Fritz, University of Nebraska - Lincoln