prevalencePower
Power analysis for establishing a prevalence
This function can be used to establish how many participants are required to establish a prevalence rate with a given margin of error.
Usage
prevalencePower(expectedPrevalence, marginOfError = 0.05, conf.level = 0.95)
Arguments
 expectedPrevalence
 The expected prevalence.
 marginOfError
 The desired precision.
 conf.level
 The confidence of the confidence interval.
Details
Note that when uncertain as to the expected prevalence, it's better to assume a prevalence closer to 50%. Prevalences closer to 0% or 100% are easier to detect and therefore have more power.
Value

The required number of participants.
See Also
Examples
### Required participants for detecting a prevalence of 10%
### with a 95% confidence interval of 10% wide:
prevalencePower(.1);
### Required participants for detecting a prevalence of 10%
### with a 95% confidence interval of 4% wide:
prevalencePower(.1, .02);
### Required participants for detecting a prevalence of 60%
### with a 95% confidence interval of 10% wide:
prevalencePower(.6);
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