PracTools (version 1.2.5)

nPropMoe: Simple random sample size for a proportion based on margin of error

Description

Calculates a simple random sample size based on a specified margin of error.

Usage

nPropMoe(moe.sw, e, alpha = 0.05, pU, N = Inf)

Arguments

moe.sw

switch for setting desired margin of error (1 = CI half-width on the proportion; 2 = CI half-width on a proportion divided by \(p_U\))

e

desired margin of error; either \(e=z_{1-\alpha/2}\sqrt{V(p_s)}\) or \(e=z_{1-\alpha/2}CV(p_s)\)

alpha

1 - (confidence level)

pU

population proportion

N

number of units in finite population

Value

numeric sample size

Details

The margin of error can be set as the half-width of a normal approximation confidence interval, \(e=z_{1-\alpha/2}\sqrt{V(p_s)}\), or as the half-width of a normal approximation confidence interval divided by the population proportion, \(e=z_{1-\alpha/2}CV(p_s)\). The type of margin of error is selected by the parameter moe.sw where moe.sw=1 sets \(e=z_{1-\alpha/2}\sqrt{V(p_s)}\) and moe.sw=2 sets i.e., \(e=\frac{z_{1-\alpha/2}\sqrt{V(p_s)}}{p_U}\).

References

Valliant, R., Dever, J., Kreuter, F. (2018, chap. 3). Practical Tools for Designing and Weighting Survey Samples, 2nd edition. New York: Springer.

See Also

nCont, nLogOdds, nProp, nWilson

Examples

# NOT RUN {
# srs sample size so that half-width of a 95% CI is 0.01
# population is large and population proportion is 0.04
nPropMoe(moe.sw=1, e=0.01, alpha=0.05, pU=0.04, N=Inf)

# srswor sample size for a range of margins of error defined as
# half-width of a 95% CI
nPropMoe(moe.sw=1, e=seq(0.01,0.08,0.01), alpha=0.05, pU=0.5)

# srswor sample size for a range of margins of error defined as
# the proportion that the half-width of a 95% CI is of pU
nPropMoe(moe.sw=2, e=seq(0.05,0.1,0.2), alpha=0.05, pU=0.5)
# }