Abstract
Measurement of subjective animal welfare creates a special problem in validating the measurement indicators. Validation is required to ensure indicators are measuring the intended target state, and not some other object. While indicators can usually be validated through looking for correlation between target and indicator under controlled manipulations, this is not possible when the target state is not directly accessible. In this paper, I outline a four-step approach using the concept of robustness, that can help with validating indicators of subjective animal welfare.
