Provide examples of how you addressed feasibility and statistical versus clinical significance in your proposal. For example, why did you select a four-week time frame for your project versus a power analysis? Did you select this because it was feasible? Why or why not and explain.

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Let’s consider a hypothetical research project on the effectiveness of a new weight-loss intervention program. This research questions is about whether or not the program results in significant weight loss in overweight persons compared to a group that does not have it.

Feasibility is a function of many factors. These include the resources available, the time required, as well as the feasibility of the research. For example, when a program is designed to help people lose weight, feasibility can be determined by how many participants are available and how much money they have.

If the researcher wishes to study a population difficult to reach, the feasibility of such a study may be restricted. It may also not be possible to conduct the study if it requires long-term interventions. To increase feasibility, the researcher might opt to have the intervention last for four weeks.

Clinical significance versus statistical significance. Statistical significance is the likelihood that an observed effect was not caused by chance. On the other side, clinical significance is the relevance of the observed effect in practice.

The researcher might choose to conduct a weight loss intervention program over a period of four weeks based on feasibility. However, he or she may also do a power analysis in order to determine if the sample is large enough to show statistically significant differences between intervention and control.

But, just because statistical significance is significant does not mean that it will be clinically important. Even if statistically significant, the effect may be too small to have clinical significance. The researcher might need to assess the clinical significance of the effect by considering whether or not the difference in bodyweight is relevant to the population.

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