What is Statistical significance and p-value ?

What is Statistical significance and p-value ?

Statistical significance and p-value - Statistical significance or stat sig is widely used in medical research. Simply put, it tells us how likely it is that x caused y, where x is the drug and y is the treatment benefit observed in a trial. It is important to understand that this differs from clinical significance. A drug could have caused statistically significant treatment benefit, but yet may not be clinically significant. This means, it is likely that the drug, not pure chance, caused the treatment benefit. Yet, the benefit was not “good enough” to forego existing treatment methods for this new one. That comparison - that of clinical significance - cannot be done simply by comparing numbers for stat sig. A host of other factors depending on the disease, the patient population, safety, etc, are required to determine clinical significance.

p-value is one of the measures of stat sig. A p-value is a complex statistical parameter calculated from a “chi-square” table. A chi-square table gives a quantified measure of the difference between observed value and expected value for each instance in a trial. In p-value, the “p” stands for probability, the probability that an observed difference happened purely by chance (the null hypothesis). The higher the p-value, the more likely it is that the observed difference - in our case, the treatment benefit - occurred due to chance rather than due to the drug being tested.

For our purpose, what we need to understand is that, in any clinical trial, the p-value is set at 0.05 as the borderline measure for stat sig. Anything lower than 0.05 means it is likely that the drug had benefit. If the p-value is under .01, results are considered statistically significant and if it's below .005 they are considered highly statistically significant.

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