n.MAS {ProbSamplingI}

Sample Size Using Simple Random Sampling Design Without Replacement

Description

The n.MAS function determines the sample size by a simple random sample design without replacement, taking into account whether the parameter of interest is the mean (or total) or a proportion.

Usage

n.MAS(N,Argt,Nc=0.95,opc=2)

# n.MAS(N,Argt=c(S,Emax.a),opc=1,Nc=0.95)
# n.MAS(N,Argt=c(Cve,Emax.r),opc=2,Nc=0.95)
# n.MAS(N,Argt=c(p,Emax.a),opc=3,Nc=0.95)
# n.MAS(N,Argt=c(p,Emax.r),opc=4,Nc=0.95)

Arguments

N

Population size.

opc

Numeric value from 1 to 4, which indicates the option to choose.

Argt

Vector of length two, in which its components depends on the chosen option ("opc"). If option 1, (opc = 1) is chosen, the components of the Argt vector are in their order, the standard deviation of the variable of interest and the respective absolute maximum error that can be admitted; If option 2 (opc = 2) is chosen, the components of the Argt vector are respectively the estimated coefficient of variation and the relative maximum error to be controlled; If option 3 (opc = 3) is chosen, the components are the estimated proportion and absolute maximum error that can be admitted; And if option 4 (opc = 4) is chosen, the components are the estimated ratio and the relative maximum error respectively.

Nc

Confidence level (between 0 and 1) that you want to set.

Value

This function returns the sample size through the conditions set in the arguments.

Author(s)

Jorge Alberto Barón Cárdenas <[e-mail]>

Guillermo Martínez Flórez <[e-mail]>

References

Särndal, C. E., J. H. Wretman, and C. M. Cassel (1992). Foundations of Inference in Survey Sampling. Wiley New York.

Cochran, W. G. (1977). Sampling Techniques, 3ra ed. New York: Wiley.

Thompson, S. K. (1945). Wiley Series in Probability and Statistics, Sampling, 1ra ed. United States of America.

Examples

# Sample size for the mean (or total) when you want to control the absolute maximum error.

Nc<-0.95
S<-sqrt(6.0590)
Emax.a<-0.2
N<-10000
n.MAS(N=N,Argt=c(S,Emax.a),opc=1)


# Sample size for the mean (or total) when you want to control the relative maximum error.

Cve<-0.4346
Emax.r<-0.05
N<-10000
n.MAS(N=N,Argt=c(Cve,Emax.r))

# Sample size for proportions when you want to control the absolute maximum error.

N<-10000
p<-14/30
Emax.a<-0.04
Nc<-0.9
n.MAS(N=N,Argt=c(p,Emax.a),opc=3,Nc=Nc)

# Sample size for proportions when you want to control the relative maximum error.

N<-10000
p<- 14/30
Emax.r<-0.1
Nc<-0.9
n.MAS(N=N,Argt=c(p,Emax.r),opc=4,Nc=Nc)