Review External Data

The CMC model predicts serum IgG concentration from user-defined colostrum management practices. An important question is how these predictions compare with previously published research.

The Review External Data utility compares CMC predictions with four published serum IgG prediction models:

• Chigerwe et al. 
• Kruse et al. (RDM equation) 
• Kruse et al. (SDM equation) 
• Osaka et al. 

These equations were developed from independent research populations using different calves, management systems, and statistical approaches. Agreement between CMC and these published models provides an additional assessment of model performance across a wide range of conditions.

How the comparison works

The utility imports a spreadsheet containing calf-level information for each animal. Required variables include information such as:

• Birth weight 
• Colostrum IgG concentration 
• Feeding volume 
• Feeding age 
• Additional feedings (if present) 
• Pasteurization status 
• Heat stress status 

CMC calculates the predicted serum IgG concentration for every calf using the selected CMC equation.

The same calf data are then evaluated using each published prediction equation. Summary statistics are calculated to compare the published predictions with those generated by CMC.

Typical output includes measures such as:

• Mean prediction difference 
• Standard deviation of differences 
• Median difference 
• Mean absolute error (MAE) 
• Root mean square error (RMSE) 
• Correlation between predictions 

Why this comparison is useful

No prediction equation is considered a perfect reference standard. Instead, agreement among independently developed models provides confidence that CMC is producing biologically reasonable predictions.

These comparisons are intended for research and model validation rather than routine farm decision making.