quantitative differences
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Clinical significance involves a decision that is made based on the practical experience value or relevance of a particular treatment. Clinical significance does not necessarily involve statistical significance as an initial criterion (Friedman, 2014).
On the other hand, statistical significance involves an outcome of research that can be indicated to be true. This differs from clinical significance that can be said to be a subjective interpretation of the results from research that only offers practical experience to a patient (Peake, 2013). Further, statistical significance involves large sample size in research analysis while clinical significance only requires minimal size. While statistical significance research requires more time, effort and high costs, clinical significance does not need much time or money to be carried out (Friedman, 2014).
Additionally, clinical significance is used to describe the effects of the treatment of disease while statistical significance is not. Statistical significance further occurs along a continuum while clinical significance looks at quantitative differences between groups sample of the population is due to chance. If statistical significance is not carried out correctly such as using a large amount of sample, random errors will increase and resulting in incorrect results. However, clinical significance does not depend on correct data as the results can be reported using risk measures (Peake, 2013).
