Sample size to estimate a continuous outcome using a stratified random sampling design
Sample size to estimate a continuous outcome using a stratified random sampling design.
epi.ssstrataestc(strata.n, strata.xbar, strata.sigma, epsilon.r, nfractional = FALSE, conf.level = 0.95)
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. |
A list containing the following:
strata.sample |
the estimated sample size for each strata. |
strata.total |
the estimated total size. |
strata.stats |
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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).
Levy PS, Lemeshow S (1999). Sampling of Populations Methods and Applications. Wiley Series in Probability and Statistics, London, pp. 175 - 179.
## 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, 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%.
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