Menu location: Analysis_Sample Size_Independent Cohort.
This function gives the minimum number of case subjects required to detect a true relative risk or experimental event rate with power POWER and two sided type I error probability ALPHA. This sample size is also given as a continuity-corrected value intended for use with corrected chi-square and Fisher's exact tests (Casagrande et al. 1978; Meinert 1986; Fleiss, 1981; Dupont, 1990).
Information required
POWER: probability of detecting a real effect
ALPHA : probability of detecting a false effect (two sided: double this if you need one sided)
P0 : probability of event in controls
*input either P1 or RR, where RR=P1/P0
P1: probability of event in experimental subjects
RR : relative risk of events between experimental subjects and controls
M : number of control subjects per experimental subject
Practical issues
Usual values for POWER are 80%, 85% and 90%; try several in order to explore/scope.
5% is the usual choice for ALPHA.
P0 can be estimated as the population prevalence of the event under investigation.
If possible, choose a range of relative risks that you want have the statistical power to detect.
Technical validation
The estimated sample size n is calculated as:
- where a = alpha, b = 1 - power, nc is the continuity corrected sample size and Zp is the standard normal deviate for probability p. n is rounded up to the closest integer.