In general, the more one knows about the wider population or context of the research problem, the easier it is to justify use of nonprobabilistic sampling. Measurement is a research step related to sampling and the estimates derived from it. In general, one should attempt to obtain measures that are meaningful, and this means interval or ratio level , especially if one is going to infer causality. Validity and reliability refer, respectively, to whether one is measuring what one intends to measure and if one is doing it consistently. These qualities of research, as well as the general idea of sampling, demonstrate inference by streamlining a project into manageable and meaningful proportions.
Design issues depend, in large part, upon the expertise and creativity of the researcher.
What one wants is a good tradeoff between a parsimonious design and one that provides the highest level of confidence. Of course, this depends upon the type of questions asked and relationships predicted. Designing with confidence does not refer to the power of statistical estimates, although there is such a thing as statistical correspondence validity which means that the intended analysis is consistent with the design to be used. Confidence , as the term means here, simply means that the prospective design is one the researcher feels comfortable with and is likely to be appreciated by the rest of the scientific community. This is often referred to as the requirement of replication .