B The probability is determined by the type-II error of the study
Before a study is conducted, the researcher must select the significance level (a), which is the value used to interpret the result of the statistical test. The a level represents the probability that the statistical test used will detect a clinically significant difference due to chance alone. This is the chance of a type-I error. The a level does not predict the response of an individual patient, or the proportion of a sample that will have a particular therapeutic outcome.
The probability of a statistical test failing to detect a difference between means of two samples when such a difference truly exists, is the b or type-II error. As the level of significance increases, there is a greater chance of a type-I error, but less chance of a type II error, therefore, b decreases as a increases.
The ability of a statistical test to detect a difference between two means is the power of the test. Power is the probability that a statistical test will detect a difference when such a difference truly exists and is not due to chance. Power is the complement of b, and is equal to 1-b. Therefore, b decreases as power increases. As the level of significance, and the chance of a type-I error decreases, b increases. Power differs from a and b in that it is not a measure of error.