Simple random sample size for a proportion based on margin of error
Calculates a simple random sample size based on a specified margin of error.
nPropMoe(moe.sw, e, alpha = 0.05, pU, N = Inf)
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-α/2}√{V(p_s)} or e=z_{1-α/2}CV(p_s) |
alpha |
1 - (confidence level) |
pU |
population proportion |
N |
number of units in finite population |
The margin of error can be set as the half-width of a normal approximation
confidence interval, e=z_{1-α/2}√{V(p_s)}, or as the half-width
of a normal approximation confidence interval divided by the population proportion,
e=z_{1-α/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-α/2}√{V(p_s)} and moe.sw=2 sets i.e., e=\frac{z_{1-α/2}√{V(p_s)}}{p_U}.
numeric sample size
Richard Valliant, Jill A. Dever, Frauke Kreuter
Valliant, R., Dever, J., Kreuter, F. (2013, chap. 3). Practical Tools for Designing and Weighting Survey Samples. New York: Springer.
# 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)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.