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Chris Donovan, Dr. Trisha Shrum

September 21, 2025

Introduction

This is the repository for the Repeated Environmental Behavior Latent (REBL) Scale project. It contains all the code to build the REBL scale from raw data through visualizations.

Installing REBL

To install the rebl package:

if (!require('remotes')) install.packages('remotes')
remotes::install_github('ChrisDonovan307/rebl')

See vignette for an example of how to use the package.

Using REBL

To get REBL Scores, we first identify our REBL items as a character vector. If you already have this handy, you can skip this step. Next, we select a model to run and get a model object. Finally, we wrangle REBL Scores from the model.

library(rebl)

rebl_items <- id_rebl_items(
  df = example, 
  pattern = '^(?!res).*', 
  perl = TRUE
)

model_cml <- get_rasch_model(
  df = example, 
  id = 'respondent_id', 
  rebl_items = rebl_items,
  type = 'cml'
)

rebl_scores <- get_rebl_scores(model = model_cml)
head(rebl_scores)

See the vignettes for details on how to use REBL Score to measure pro-environmental behavior using different model types as well as model validation.

REBL Calculator

There is also a REBL Score Calculator that will take a dataset and produce all the results you might need for you. Note that it currently has a limited range of applications, but will be updated with more features and broader use cases shortly.

Coming Soon

  • Model validation: reliability and invariance
  • Model outputs and GoF
  • Test linking to baseline