Which term refers to the degree to which a model accurately reflects or measures what it is intended to?

The term that accurately reflects the concept of how well a model measures or represents what it is intended to is validity. In this context, valid measurements refer to the degree to which the results of the model align with the actual qualities or characteristics they are supposed to represent. This is crucial in fields such as statistics, science, and social research, as it ensures that the conclusions drawn from a model are based on accurate representations of the variables involved.

In contrast, model strength refers to the effectiveness of the model in making predictions but does not specifically address whether it accurately reflects its intended measures. Extrapolated data involves extending the results beyond the range of the original data set, which does not directly relate to the model's validity. Model robustness refers to the ability of the model to perform well under varied conditions or with different data sets, again not directly measuring the accuracy of representation. Valid measurements are central to determining the effectiveness of any model in research or applied mathematics, making this the correct concept to address the question.