Stats Power

Question 1

Power

Answer 1

The power of a study is the probability of (correctly) rejecting the null hypothesis when it is false (i.e. it will not make a Type II error).

Basically we use the power to help us decide how many people need to be recruited in a study in order to detect a clinically meaningful difference or effect.

Power can assume values between 0 and 1 (Since probability values are expressed by numbers between 0 and 1 only). Sometimes it is expressed as a percentage - 0 referring to 0 %, and 1 referring to 100 %.

Power is expressed as 1 - beta, where beta is the probability of a Type II error. A power 0.80 is often seen as the level of minimum acceptability.

Question 2

Power is influenced by the following:-

Answer 2

Sample size (larger samples lead to parameter estimations of smaller variance and therefore increase the study's ability to detect a significant effect
Meaningful effects size (this has to be decided at the beginning of a study, it is the size of the difference between two means that lead you to reject the null hypothesis)
Significance level (aka the alpha level, which is the probability of a type I error)

Question 3

Power

Answer 3

The power of a study is the probability of (correctly) rejecting the null hypothesis when it is false

Power = 1 - the probability of a type II error
Power can be increased by increasing the sample size