e4dm: Statistical errors for the estimation of a difference of...
In samplesize4surveys: Sample Size Calculations for Complex Surveys

Description Usage Arguments Details Value Author(s) References See Also Examples

This function computes the cofficient of variation and the standard error when estimating a difference of means under a complex sample design.

1	e4dm(N, n, mu1, mu2, sigma1, sigma2, DEFF = 1, conf = 0.95, plot = FALSE)

`N`	The population size.
`n`	The sample size.
`mu1`	The value of the estimated mean of the variable of interes for the first population.
`mu2`	The value of the estimated mean of the variable of interes for the second population.
`sigma1`	The value of the estimated variance of the variable of interes for the first population.
`sigma2`	The value of the estimated mean of a variable of interes for the second population.
`DEFF`	The design effect of the sample design. By default `DEFF = 1`, which corresponds to a simple random sampling design.
`conf`	The statistical confidence. By default `conf = 0.95`.
`plot`	Optionally plot the errors (cve and margin of error) against the sample size.

We note that the coefficent of variation is defined as:

cve = \frac{√{Var(\bar{y}_1 - \bar{y}_2)}}{\bar{y}_1 - \bar{y}_2}

Also, note that the magin of error is defined as:

\varepsilon = z_{1-\frac{α}{2}}√{Var(\bar{y}_1 - \bar{y}_2)}

The coefficient of variation and the margin of error for a predefined sample size.

Hugo Andres Gutierrez Rojas <hagutierrezro at gmail.com>

Gutierrez, H. A. (2009), Estrategias de muestreo: Diseno de encuestas y estimacion de parametros. Editorial Universidad Santo Tomas

ss4p

1
2
3

e4dm(N=10000, n=400, mu1 = 100, mu2 = 12, sigma1 = 10, sigma2=8)
e4dm(N=10000, n=400, mu1 = 100, mu2 = 12, sigma1 = 10, sigma2=8, plot=TRUE)
e4dm(N=10000, n=400, mu1 = 100, mu2 = 12, sigma1 = 10, sigma2=8, DEFF=3.45, conf=0.99, plot=TRUE)