Study conducted at Armstrong Equine Center and NMZU horse farm with water sourced from both locations.
Experimental Design
Subjects: 12 mares
Random Assignment: Mares assigned to two treatments.
Period One:
6 mares (identified as group 6A) assigned to treatment one (water from NMSU horse farm).
6 mares (identified as group 6B) assigned to treatment two (water from Armstrong).
Period Two:
The mares that received treatment one in period one (6A) received treatment two in period two.
The mares that received treatment two in period one (6B) received treatment one in period two.
Treatment Objective
Objective was to induce thirst upon arrival by providing water from specified sources.
Blocking Mechanisms
Period as Blocking Factor: Period one and period two can be viewed as distinct blocks.
Treatment as Blocking Factor: The different water sources also serve as blocking factors.
Experimental Units and Interaction Testing
Units: 12 mares
Blocking consideration suggests that 12 experimental units minus one (degrees of freedom associated with experimental design).
Interaction Testing: Interaction between period and treatment is something that could be explored, although in this study, direct interaction testing may not have been conducted due to complexity.
Design Analysis
Aim to remove variability to yield cleaner evidence for stronger conclusions based on treatment effects.
Recognized differences between crossover designs and Latin square designs.
Crossover Design: Each horse becomes its own control, allowing it to experience both treatments across periods, controlling for individual variability (e.g., age, first treatment effects).
Latin Square Design: Considers interactions but can lead to loss of degrees of freedom due to the complexity of managing multiple treatments.
Benefits of Crossover Design
Allows for greater sensitivity and control over variability inherent to individual horses (variability in age, weight, etc.).
Helpful when available animals are heterogeneous (different ages/sizes), as it allows powerful conclusions to be drawn even with fewer uniform animals.
Managing Carryover Effects
To mitigate carryover effects in crossover studies, it is crucial to include an adaptation period when switching treatments (at least 10 days in this context).
Data Analysis
Data Collection: Specific water consumption in kilograms per day recorded for each animal and treatment.
Consumption per horse and across treatments totaled:
Period One water consumption ranged (sample values):
Period Two switched treatment sources, data collection strategy remained consistent.
Statistical Treatment of Data
Total water consumption calculated by summing across periods:
Example total for one horse might have been computed, yielding totals 72.3 (specific values to be calculated by participants).
Total mean sum of squares calculated, with components related to:
Horse effect, treatment effect, period effect, and residual variance.
F-values calculated for treatment and interactions to determine statistical significance:
Formula used: F = \frac{\text{Mean Sum of Squares Treatment}}{\text{Mean Sum of Squares Error}}
Results Interpretation
Examined p-values to assess significance of treatment effects; p-values greater than thresholds indicated no significant difference in water consumption based on treatment.
Recognized general rule of thumb: If the difference between two means exceeds double the standard error, it suggests significance. However, due to data outcomes, this rule did not hold in the case of the study.
Conclusion
Final determination made based on analysis: water source has no significant effect on water consumption in mares, demonstrating effectiveness of the crossover design in yielding clear evidence despite inherent variability in horse populations.