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. The research question is whether the program can lead to a significant reduction in body weight in overweight individuals compared to a control group.

Feasibility: The feasibility of a research project depends on several factors, including the availability of resources, time, and the practicality of conducting the study. In the case of the weight-loss intervention program, the feasibility of the study could be determined by factors such as the availability of participants, the funding required for the program, and the duration of the study.

For instance, if the researcher wants to conduct the study in a population that is difficult to reach, then the feasibility of the study might be limited. Additionally, if the proposed study requires a long-term intervention program, it may not be feasible due to time and financial constraints. In this case, the researcher may opt for a shorter intervention period, say four weeks, to increase the feasibility of the study.

Statistical versus clinical significance: Statistical significance refers to the probability that the observed effect in the study is not due to chance. Clinical significance, on the other hand, refers to the practical relevance of the observed effect.

In the case of the weight-loss intervention program, the researcher may choose a four-week time frame for the intervention based on feasibility but also perform a power analysis to ensure that the sample size is sufficient to detect a statistically significant difference between the intervention and control groups.

However, statistical significance alone may not necessarily imply clinical significance. For example, if the observed effect size is small, even if it is statistically significant, it may not be clinically meaningful. Therefore, the researcher may need to consider the clinical relevance of the effect size by determining whether the observed difference in body weight is meaningful to the target population.