Bayesian Sample Size Calculations for Calf Pneumonia Diagnostic Trial

A dataset from Borealis Harvested Dataverse shows the effect of different parameter values on sample size calculations for a diagnostic accuracy trial. The trial aims to evaluate a clinical scoring system and lung ultrasound for diagnosing pneumonia in pre-weaned dairy calves. The data was authored by Katheryn Churchill and last updated on June 13, 2026.

Use Cases

• Planning diagnostic trial sample sizes based on expected disease prevalence.
• Sensitivity analysis for Bayesian latent-class models based on parameter inputs.
• Evaluating diagnostic thresholds for clinical scoring systems based on continuous variables.
• Estimating optimal weights for combined case definitions based on clinical and ultrasound data.

Strengths

• Dataset is associated with a formal trial protocol for diagnostic accuracy.
• Focuses on a specific, well-defined veterinary health problem (pre-weaned calf pneumonia).
• Last updated date is explicitly provided (2026-06-13).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Borealis Harvested Dataverse

Collection Method

Likely generated for sample size calculations using a template from the Center for Animal Disease Modeling and Surveillance at UC Davis Veterinary Medicine.

Freshness

Last updated 2026-06-13 04:11:00