# nPropMoe: Simple random sample size for a proportion based on margin of...

### Description

Calculates a simple random sample size based on a specified margin of error.

### Usage

 1 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-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

### Details

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}.

### 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, nWilson

### Examples

  1 2 3 4 5 6 7 8 9 10 11 # 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) 

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