epi.sssimpleestc {epiR} | R Documentation |

Sample size to estimate a continuous outcome using simple random sampling.

epi.sssimpleestc(N = 1E+06, xbar, sigma, epsilon.r, nfractional = FALSE, conf.level = 0.95)

`N` |
scalar integer, representing the total number of individual listing units in the population. |

`xbar` |
scalar number, the expected mean of the continuous variable to be estimated. |

`sigma` |
scalar number, the expected standard deviation of the continuous variable to be estimated. |

`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. |

Returns an integer defining the required sample size.

`epsilon.r`

defines the maximum relative difference between our estimate and the unknown population value. The sample estimate should not differ in absolute value from the true unknown population parameter `d`

by more than `epsilon.r * d`

.

Levy PS, Lemeshow S (1999). Sampling of Populations Methods and Applications. Wiley Series in Probability and Statistics, London, pp. 70 - 75.

Scheaffer RL, Mendenhall W, Lyman Ott R (1996). Elementary Survey Sampling. Duxbury Press, New York, pp. 95.

Otte J, Gumm I (1997). Intra-cluster correlation coefficients of 20 infections calculated from the results of cluster-sample surveys. Preventive Veterinary Medicine 31: 147 - 150.

## EXAMPLE 1: ## A city contains 20 neighbourhood health clinics and it is desired to take a ## sample of clinics to estimate the total number of persons from all these ## clinics who have been given, during the past 12 month period, prescriptions ## for a recently approved antidepressant. If we assume that the average number ## of people seen at these clinics is 1500 per year with the standard deviation ## equal to 300, and that approximately 5% of patients (regardless of clinic) ## are given this drug, how many clinics need to be sampled to yield an estimate ## that is within 20% of the true population value? pmean <- 1500 * 0.05; psigma <- (300 * 0.05) epi.sssimpleestc(N = 20, xbar = pmean, sigma = psigma, epsilon.r = 0.20, nfractional = FALSE, conf.level = 0.95) ## Four clinics need to be sampled to meet the requirements of the survey. ## EXAMPLE 2: ## We want to estimate the mean bodyweight of deer on a farm. There are 278 ## animals present. We anticipate the mean body weight to be around 200 kg ## and the standard deviation of body weight to be 30 kg. We would like to ## be 95% certain that our estimate is within 10 kg of the true mean. How ## many deer should be sampled? epi.sssimpleestc(N = 278, xbar = 200, sigma = 30, epsilon.r = 10 / 200, nfractional = FALSE, conf.level = 0.95) ## A total of 31 deer need to be sampled to meet the requirements of the survey.

[Package *epiR* version 2.0.31 Index]