# nContMoe: Compute a simple random sample size for an estimated mean of... In PracTools: Tools for Designing and Weighting Survey Samples

## 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

 1 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-α/2}√{V(\bar{y}_s)} or e=z_{1-α/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. (2013, chap. 3). Practical Tools for Designing and Weighting Survey Samples. New York: Springer.

nCont, nLogOdds, nProp, nPropMoe, nWilson
 1 2 3 4 5 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)