nContMoe | R Documentation |

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.

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

`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 |

`e` |
desired margin of error; either |

`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 |

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.

numeric sample size

Richard Valliant, Jill A. Dever, Frauke Kreuter

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

`nCont`

, `nLogOdds`

, `nProp`

, `nPropMoe`

, `nWilson`

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)

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