Half the price, twice the gain: How to simultaneously decrease animal numbers and increase precision with good...

Area of Science:

• Experimental design
• Animal research methodology
• Statistical analysis in science

Background:

• Animal research frequently examines multiple factors influencing outcomes.
• Current common practice involves one-factor-at-a-time experiments, leading to inefficiency.
• This traditional approach limits research questions and increases animal usage.

Purpose of the Study:

• To introduce factorial designs and analyses as a more efficient alternative in animal research.
• To illustrate the principles of factorial experimental design.
• To guide the design and analysis of complex experiments with multiple factors.

Main Methods:

• Explanation of fundamental factorial design principles.
• Demonstration using a two-factor experimental example.
• Guidance on multiway analysis of variance for complex designs.

Main Results:

• Factorial designs are more efficient than one-factor-at-a-time approaches.
• Factorial designs enable answering broader research questions.
• Multiway analysis of variance is suitable for complex factorial experiments.

Conclusions:

• Factorial designs offer a statistically sound and resource-efficient method for animal experiments.
• Adopting factorial designs can significantly advance scientific understanding while minimizing animal use.
• This methodology is crucial for modern, efficient biological research.