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Implementing structural equation models to observational data from feedlot production systems.

Elva Cha1, Mike Sanderson1, David Renter1

  • 1Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA; Center for Outcomes Research and Epidemiology (CORE), College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.

Preventive Veterinary Medicine
|December 20, 2017
PubMed
Summary

Structural equation modeling (SEM) in feedlots reveals arrival weight directly boosts average daily gain (ADG) and indirectly impacts ADG through Bovine Respiratory Disease (BRD) treatment costs. This method distinguishes direct and indirect effects for better production insights.

Keywords:
Bovine respiratory diseaseDirect and indirect effectsFeedlot cattleStructural equation modeling

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Area of Science:

  • Animal Science
  • Agricultural Economics
  • Statistical Modeling

Background:

  • Bovine Respiratory Disease (BRD) significantly impacts feedlot morbidity and mortality, affecting production efficiency.
  • Understanding the complex relationships between animal health and performance is crucial for optimizing feedlot operations.
  • Traditional models may not fully capture the direct and indirect pathways influencing feedlot performance.

Purpose of the Study:

  • To implement and illustrate a mixed-model-based structural equation modeling (SEM) approach for analyzing observational data in feedlot production systems.
  • To assess the direct and indirect effects of arrival weight (AW) on average daily gain (ADG), mediated by Bovine Respiratory Disease (BRD) treatment costs (Trt$).
  • To compare SEM-derived effect estimates with those from standard linear regression mixed models.

Main Methods:

  • Utilized a dataset of 1430 lots (178,983 cattle) from 9 US Great Plains feedlot operations.
  • Employed structural equation modeling (SEM) to analyze functional links between arrival weight (AW), BRD-related treatment costs (Trt$), and average daily gain (ADG).
  • Accounted for fixed effects of sex and clustered correlations within feedlots using a mixed-model framework.

Main Results:

  • The best-fitting SEM model indicated that AW had a direct positive effect on ADG (λˆ31=0.002±0.0001 kg/head/day).
  • AW also had a direct negative effect on Trt$ (λˆ21=$0.08±0.006 USD/head), and increased Trt$ directly decreased ADG (λˆ32=0.004±0.0006 kg/head/day).
  • SEM effectively distinguished direct and indirect pathways, providing a more nuanced understanding than standard regression models.

Conclusions:

  • Mixed-model SEM provides a robust framework for dissecting complex causal interrelationships in feedlot production data.
  • Arrival weight influences average daily gain both directly and indirectly through its impact on health-related treatment costs.
  • Understanding these direct and indirect mechanisms is vital for improving feedlot health management and overall production efficiency.