epiR (version 1.0-15)

epi.ssstrataestc: Sample size to estimate a continuous outcome using a stratified random sampling design

Description

Sample size to estimate a continuous outcome using a stratified random sampling design.

Usage

epi.ssstrataestc(strata.n, strata.xbar, strata.sigma, epsilon.r, 
   conf.level = 0.95)

Arguments

strata.n

vector of integers, defining the number of individual listing units in each strata.

strata.xbar

vector of numbers, defining the expected means of the continuous variable to be estimated for each strata.

strata.sigma

vector of numbers, defining the expected standard deviation of the continous variable to be estimated for each strata.

epsilon.r

scalar number, the maximum relative difference between the estimate and the unknown population value.

conf.level

scalar number, the level of confidence in the computed result.

Value

A list containing the following:

strata.sample

the estimated sample size for each strata.

strata.total

the estimated total size.

strata.stats

mean the mean across all strata, sigma.bx the among-strata variance, sigma.wx the within-strata variance, and sigma.x the among-strata variance plus the within-strata variance, rel.var the within-strata variance divided by the square of the mean, and gamma the ratio of among-strata variance to within-strata variance.

References

Levy PS, Lemeshow S (1999). Sampling of Populations Methods and Applications. Wiley Series in Probability and Statistics, London, pp. 175 - 179.

Examples

# NOT RUN {
## EXAMPLE 1:
## Hospital episodes (Levy and Lemeshow 1999, page 176 -- 178)
## We plan to take a sample of the members of a health maintenance 
## organisation (HMO) for purposes of estimating the average number
## of hospital episodes per person per year. The sample will be selected
## from membership lists according to age (under 45 years, 45 -- 64 years, 
## 65 years and over). The number of members in each strata are 600, 500,
## and 400 (respectively). Previous data estimates the mean number of 
## hospital episodes per year for each strata as 0.164, 0.166, and 0.236
## (respectively). The variance of these estimates are 0.245, 0.296, and 
## 0.436 (respectively). How many from each strata should be sampled to be
## 95% that the sample estimate of hospital episodes is within 20% of the 
## true value?

strata.n <- c(600, 500, 400)
strata.xbar <- c(0.164, 0.166, 0.236)
strata.sigma <- sqrt(c(0.245, 0.296, 0.436))
epi.ssstrataestc(strata.n, strata.xbar, strata.sigma, epsilon.r = 0.20, 
   conf.level = 0.95)

## The number allocated to the under 45 years, 45 -- 64 years, and 65 years 
## and over stratums should be 223, 186, and 149 (a total of 558). These 
## results differ from the worked example provided in Levy and Lemeshow where 
## certainty is set to approximately 99%.

# }