# Sample Size for Independent Cohort Studies

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 α = alpha, β = 1 - power, n_{c} is the continuity corrected sample size and z_{p} is the standard normal deviate for probability p. n is rounded up to the closest integer.