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.

Keywords
~kwd1 , ~kwd2
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

convert.percentage.to.se

Aliases
  • prevalencePower
Examples
# NOT RUN {
### 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);
# }
Documentation reproduced from package userfriendlyscience, version 0.6-1, License: GPL (>= 2)

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