nPropMoe {PracTools}

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

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}.

Value

numeric sample size

Author(s)

Richard Valliant, Jill A. Dever, Frauke Kreuter

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

# 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)