nContMoe {PracTools}

Compute a simple random sample size for an estimated mean of a continuous variable based on margin of error

Description

Compute a simple random sample size using a margin of error specified as the half-width of a normal approximation confidence interval or the half-width relative to the population mean.

Usage

nContMoe(moe.sw, e, alpha=0.05, CVpop=NULL, S2=NULL, ybarU=NULL, N=Inf)

Arguments

moe.sw

switch for setting desired margin of error (1 = CI half-width on the mean; 2 = CI half-width on the mean divided by \bar{y}_U)

e

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

alpha

1 - (confidence level)

CVpop

unit (population) coefficient of variation

S2

population variance of the target variable

ybarU

population mean of target variable

N

number of units in finite population

Details

If moe.sw=1, then S2 must be provided. If moe.sw=2, then either (i) CVpop or (ii) S2 and ybarU must be provided.

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, nPropMoe, nWilson

Examples

nContMoe(moe.sw=1, e=0.05, alpha=0.05, S2=2)
nContMoe(moe.sw=1, e=0.05, alpha=0.05, S2=2, N=200)
nContMoe(moe.sw=2, e=0.05, alpha=0.05, CVpop=2)
nContMoe(moe.sw=2, e=0.05, alpha=0.05, CVpop=2, N=200)
nContMoe(moe.sw=2, e=0.05, alpha=0.05, S2=4, ybarU=2)