What is Power Analysis?

Power Analysis is an important aspect of experimental design. It allows us to determine the sample size required to detect an effect of a given size with a given degree of confidence.
There are four parameters involved in a power analysis.  The research must ‘know’ 3 and solve
for the 4th.
1. Alpha:
 Probability of finding significance where there is none
 False positive
 Probability of a Type I error
 Usually set to.05
2. Power
 Probability of finding true significance
 True positive
 1 – beta, where beta is:
 Probability of not finding significance when it is there
 False negative
 Probability of a Type II error
 Usually set to.80
3. N:
 The sample size (usually the parameter you are solving for)
 May be known and fixed due to study constraints
4. Effect size:
 Usually, the ‘expected effect’ is ascertained from:
 Pilot study results
 Published findings from a similar study or studies
 May need to be calculated from results if not reported
 May need to be translated as design specific using rules of thumb
 Field defined ‘meaningful effect’
 Educated guess (based on informal observations and knowledge of the
field)

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