Description Usage Arguments Details Author(s) References See Also Examples
This function returns the minimum sample size required for testing a null hyphotesis regarding a single mean
1 |
N |
The population size. |
mu |
The population mean of the variable of interest. |
mu0 |
The value to test for the single mean. |
sigma |
The population variance of the variable of interest. |
DEFF |
The design effect of the sample design. By default |
conf |
The statistical confidence. By default |
power |
The statistical power. By default |
plot |
Optionally plot the effect against the sample size. |
We assume that it is of interest to test the following set of hyphotesis:
H_0: mu - mu_0 = 0 \ \ \ \ vs. \ \ \ \ H_a: mu - mu_0 = D \neq 0
Note that the minimun sample size, restricted to the predefined power β and confidence 1-α, is defined by:
n = \frac{S^2}{\frac{D^2}{(z_{1-α} + z_{β})^2}+\frac{S^2}{N}}
Where S^2=σ^2 * DEFF and σ^2 is the population variance of the varible of interest.
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ss4mH(N = 10000, mu = 500, mu0 = 505, sigma = 100)
ss4mH(N = 10000, mu = 500, mu0 = 505, sigma = 100, plot=TRUE)
ss4mH(N = 10000, mu = 500, mu0 = 505, sigma = 100, DEFF = 2, plot=TRUE)
ss4mH(N = 10000, mu = 500, mu0 = 505, sigma = 100, conf = 0.99, power = 0.9, DEFF = 2, plot=TRUE)
#############################
# Example with BigLucy data #
#############################
data(BigLucy)
attach(BigLucy)
N <- nrow(BigLucy)
mu <- mean(Income)
sigma <- sd(Income)
# The minimum sample size for testing
# H_0: mu - mu_0 = 0 vs. H_a: mu - mu_0 = D = 15
D = 15
mu0 = mu - D
ss4mH(N, mu, mu0, sigma, conf = 0.99, power = 0.9, DEFF = 2, plot=TRUE)
# The minimum sample size for testing
# H_0: mu - mu_0 = 0 vs. H_a: mu - mu_0 = D = 32
D = 32
mu0 = mu - D
ss4mH(N, mu, mu0, sigma, conf = 0.99, power = 0.9, DEFF = 3.45, plot=TRUE)
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