Linear Mixed Model Results on Student Exam Scores by First-Generation Status

Aggregating results from a linear mixed model (LMM) analyzing student exam scores, with a focus on interactions involving first-generation status (FGN) and principal component quartiles (PC2). The dataset is 5.5 KB in size and is stored in an XLS file format.

Use Cases

• Analyze the interaction effect between First Generation Status (FGN) and PC2 quartiles on Exam Performance.
• Model the relationship between Principal Component Analysis (PCA) quartiles and student scores using the provided Linear Mixed Model results.
• Investigate how Active Learning or Students Working Alone correlates with exam outcomes as suggested by the model interactions.

Strengths

• Dataset is openly licensed under CC BY 4.0.
• Model results are focused on specific analytical interactions like FGN by PC2 quartile.
• File size of 5.5 KB indicates a concise, targeted output.

Limitations

• The dataset is very small (5.5 KB), suggesting it contains only model results, not the underlying raw data.
• No column definitions or sample data are provided, limiting immediate interpretability.
• The specific sample size (rows) and variables (columns) used in the model are unknown.

Provenance

Source

figshare

Collection Method

Results from a statistical linear mixed model analysis.

Freshness

Last updated March 20, 2026.