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A primer on intensive longitudinal psychometrics.

Daniel McNeish1

  • 1Arizona State University, Tempe, AZ, USA. dmcneish@asu.edu.

Behavior Research Methods
|April 16, 2026
PubMed
Summary
This summary is machine-generated.

This study addresses the underuse of psychometric methods in intensive longitudinal studies. It provides an overview and application examples to improve the measurement of latent constructs in psychological research.

Keywords:
Ecological momentary assessmentExperience samplingIntensive longitudinal dataMeasurementReliabilityValidity

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Area of Science:

  • Psychology
  • Quantitative Psychology
  • Psychometrics

Background:

  • Intensive longitudinal studies often measure latent constructs (e.g., emotion, personality) not directly measurable.
  • Few studies report psychometric properties for these constructs in intensive longitudinal data (15-50%).
  • Researchers lack awareness or knowledge of psychometric methods for intensive longitudinal data.

Purpose of the Study:

  • To provide an overview of intensive longitudinal psychometric methods.
  • To demonstrate the application of these psychometric methods.
  • To show how psychometric methods strengthen intensive longitudinal analyses.

Main Methods:

  • Overview of psychometric methods: reliability, construct validation, measurement invariance, and measurement error modeling.
  • Demonstration of methods with empirical examples.
  • Accompanying Shiny application and R/Mplus software walkthroughs.

Main Results:

  • Highlights the gap in psychometric reporting for latent constructs in intensive longitudinal studies.
  • Demonstrates practical application of psychometric methods.
  • Provides resources (Shiny app, code) for implementation.

Conclusions:

  • Integrating psychometric methods is crucial for accurate measurement of latent constructs in intensive longitudinal data.
  • These methods help distinguish true construct changes from measurement error.
  • The provided resources aim to increase the use of psychometrics in the field.