e4dm {samplesize4surveys}

Statistical errors for the estimation of a difference of means

Description

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

Usage

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

Arguments

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.

Details

We note that the coefficent of variation is defined as:

cve = \frac{\sqrt{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{\alpha}{2}}\sqrt{Var(\bar{y}_1 - \bar{y}_2)}

Value

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

Author(s)

Hugo Andres Gutierrez Rojas <hagutierrezro at gmail.com>

References

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

See Also

ss4p

Examples

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)