epi.ssstrataestc {epiR} R Documentation

## 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,
nfractional = FALSE, 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. `nfractional` logical, return fractional sample size. `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.

### Author(s)

Mark Stevenson (Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Australia).

Javier Sanchez (Atlantic Veterinary College, University of Prince Edward Island, Charlottetown Prince Edward Island, C1A 4P3, Canada).

### References

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

### Examples

```## EXAMPLE 1 (from 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,
nfractional = FALSE, conf.level = 0.95)

## The number allocated to the under 45 years, 45 -- 64 years, and 65 years
## and over stratums should be 224, 187, and 150 (a total of 561). These
## results differ from the worked example provided in Levy and Lemeshow where
## certainty is set to approximately 99%.

```

[Package epiR version 2.0.31 Index]