@@ -19,6 +19,15 @@ The repository is organised as follows:
## Procedure for Analysis and Replication
This section outlines the step-by-step process to analyze the data and replicate the results from the study using the scripts and dataset provided in this repository.There are 8 main steps for the replication of the analysis.
This project have used this research article "Modernizing use of regression models in physics education research: A review of hierarchical linear modeling"
This project focuses on replicating the findings of a study that critically examines the use of hierarchical linear modeling (HLM) in physics education research (PER). The original study demonstrates how single-level regression models, such as linear and logistic regression, can lead to biased findings when applied to hierarchical datasets, such as students nested within courses.
By replicating the analysis using the dataset from 112 introductory physics courses, this work confirms the significant differences between multiple linear regression and hierarchical linear modeling in handling nested data structures.
The replication validates the original conclusion that single-level models fail to account for hierarchical structures, potentially compromising the reliability of findings.
The replicated analysis reinforces the importance of using hierarchical models to produce unbiased, generalizable knowledge in PER and beyond.
The R code and sample dataset provided in the Supplemental Material of the original study were instrumental in successfully replicating these results, demonstrating the critical role of transparent, reproducible research practices.
This replication not only confirms the theoretical and practical benefits of hierarchical models but also underscores their necessity for advancing the field’s understanding of student success in physics education.
This is the APA citation of this research article: Van Dusen, B., & Nissen, J. (2019). Modernizing use of regression models in physics education research: A review of hierarchical linear modeling. Physical Review Physics Education Research, 15(2), 020108. https://doi.org/10.1103/PhysRevPhysEducRes.15.020108
