Modeling item-level heterogeneous treatment effects: A tutorial with the glmer function from the lme4 package in R

Area of Science:

• Educational Measurement
• Psychometrics
• Statistical Modeling

Background:

• Item Response Theory (IRT) models are increasingly used in educational research.
• Understanding treatment heterogeneity at the item level is crucial for accurate assessment analysis.
• Existing methods may not fully capture nuanced treatment effects on individual assessment items.

Purpose of the Study:

• To provide a comprehensive tutorial on implementing item-level heterogeneous treatment effects (IL-HTE) analysis.
• To demonstrate the application of IL-HTE models using the lme4 package in R.
• To guide applied researchers in interpreting and visualizing treatment effects at the item level.

Main Methods:

• Utilizing Item Response Theory (IRT) models for item-level heterogeneous treatment effects (IL-HTE).
• Implementing IL-HTE analysis in R, specifically with the lme4 package.
• Applying the methods to empirical data from a second-grade reading comprehension assessment.

Main Results:

• The tutorial details practical strategies for model building in IL-HTE analysis.
• It provides clear methods for interpreting the results of item-level treatment effects.
• Visualization techniques and potential extensions for IL-HTE analysis are presented.

Conclusions:

• Applied researchers can effectively use IL-HTE analysis in R for detailed assessment item evaluation.
• This approach enhances the understanding of how treatments impact individual assessment components.
• The tutorial equips researchers with practical skills for advanced treatment effect analysis in educational settings.