Counting your chickens before they're hatched: power analysis.
How does an investigator know that he has enough subjects in his study design to have the predicted outcomes appear statistically significant? In this Investigators' Corner I discuss why such planning is necessary, give an intuitive introduction to the calculations needed to determine required sample sizes, and hint at some of the more technical difficulties inherent in this aspect of study planning.
Assistant Professor, Department of Preventive Medicine and Community Health, The University of Texas Medical Branch, Galveston, TX. Electronic address: dajupite@utmb.edu.
Daniel C
DC
Jupiter
D035843:Biomedical Research / Q000592:standards*; D006801:Humans; D012107:Research Design; D018401:Sample Size
Type II error; hypothesis testing; power analysis; sample size; statistical significance