This function can be used to establish how many participants are required to establish a prevalence rate with a given margin of error.

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);
#> [1] 138.2925
### Required participants for detecting a prevalence of 10% ### with a 95% confidence interval of 4% wide: prevalencePower(.1, .02);
#> [1] 864.3282
### Required participants for detecting a prevalence of 60% ### with a 95% confidence interval of 10% wide: prevalencePower(.6);
#> [1] 368.78