computeAlphaLimitedSampling: FUNCTION to compute the average alpha-error (= error of first...
In FFD: Freedom from Disease

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/computeAlphaLimitedSampling.R

For sampling strategy "limited sampling" (see Ziller et al., 2002) the function computes the herd-level alpha-errors (= 1-herd sensitivity) for each stock size, as well as the average herd-level alpha-error.

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computeAlphaLimitedSampling(stockSizeVector, sampleSizeLtd, 
    intraHerdPrevalence, diagSensitivity, 
    diagSpecificity = 1, groupVec = NULL)

`stockSizeVector`	Integer vector. Stock sizes of the herds.
`sampleSizeLtd`	Integer. Sample size for limited sampling, i.e., for each herd `sampleSizeLtd` animals are tested, or of the herd contains less than `sampleSizeLtd` animals the entire herd is tested.
`intraHerdPrevalence`	Numeric between 0 and 1. Intra-herd prevalence. The number of diseased animals per herd is computed as `max(1,round(intraHerdPrevalence*stockSizeVector))` (it is assumed that at least one animal is diseased).
`diagSensitivity`	Numeric between 0 and 1. Sensitivity (= probability of a testpositive result, given the tested individual is diseased) of the diagnostic test.
`diagSpecificity`	Numeric between 0 and 1. Specificity (= probability of a testnegative result, given the tested individual is not diseased) of the diagnostic test.
`groupVec`	Character vector. Optional parameter. If specified it must have the same length as `stockSizeVector`. Defines the gouping of the data. Mean Alpha is then returned for each group.

List of 3 elements:

`alphaDataFrame`	Data frame. Variables `size` = vector of the unique herd sizes in the population, `alpha` = vector of herd-level alpha errors attained by limited sampling scheme for the different herd sizes.
`meanAlpha`	Numeric between 0 and 1. Mean alpha-error attained by strategy "limited sampling" for given sample size and herd size distribution.
`meanAlphaRiskGroups`	If `groupVec` is specified, the mean alpha error is returned for each group, concatenated into a vector. Otherwise this list element is NULL

Ian Kopacka <ian.kopacka@ages.at>

M. Ziller, T. Selhorst, J. Teuffert, M. Kramer and H. Schlueter, "Analysis of sampling strategies to substantiate freedom from disease in large areas", Prev. Vet. Med. 52 (2002), pp. 333-343.

computePValue

data(sheepData)
alphaList <- computeAlphaLimitedSampling(stockSizeVector = 
    sheepData$nSheep, sampleSizeLtd = 7, 
    intraHerdPrevalence = 0.2, diagSensitivity = 0.9, 
    diagSpecificity = 1)