Bayesian Hierarchical Model Results for Student Retention and Academic Advising

A dataset containing results from a Bayesian hierarchical model analyzing student retention and academic advising effects. The 5.5 KB Excel file was authored by Moeketsi Mosia and last updated on March 17, 2026. It is licensed under CC-BY-4.0 and hosted on the figshare platform.

Use Cases

• Compare the effectiveness of different academic advising interventions based on the model results.
• Analyze the relationship between academic orientation performance and subsequent year retention.
• Investigate differential treatment effects of advising across student cohorts.
• Validate or benchmark Bayesian hierarchical modeling approaches for educational administrative data.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Model results are explicitly derived using Bayesian hierarchical approaches, a specific statistical methodology.
• License is permissive (CC-BY-4.0), allowing for broad reuse and adaptation.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare, author Moeketsi Mosia.

Collection Method

Likely generated from administrative educational data using Bayesian hierarchical modeling.

Time Range

Model may reference the 2024 academic period, as suggested by platform tags.

Freshness

Last updated 2026-03-17 17:27:55; freshness should be verified.

Geography

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