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

Creates an object of the class 'LtdSampling'. For given survey parameters
(passed to the function as an object of the class `SurveyData`

)
`ltdSampling()`

computes the mean herd sensitivity, the number of herds to test,
the expected total number of animals to test and the expected total cost of a survey
using limited sampling with a given animal-level sample size `sampleSizeLtd`

.
If values for `nSampleFixVec`

and/or `probVec`

are specified, sampling
if performed with stratification of the population by risk groups.

1 2 | ```
ltdSampling(survey.Data, sampleSizeLtd, nSampleFixVec = NULL,
probVec = NULL)
``` |

`survey.Data` |
Object of class |

`sampleSizeLtd` |
Positive integer. Pre-fixed number of animals to be tested per holding, irrespective of the herd size (if the herd contains fewer animals then the entire herd needs to be tested). |

`nSampleFixVec` |
Numeric vector containing some NAs (optional argument).
For risk groups for which the sample size is fixed
specify the sample size. For the risk groups for which
the sample size should be computed set NA (order of the
risk groups must be the same order as in |

`probVec` |
Numeric vector. For those risk groups for which the
sample size should be computed sample probabilities must
be specified.
The vector must have the same length as the number of
NA entries in |

The function returns an object of the class `LtdSampling`

.

Ian Kopacka <ian.kopacka@ages.at>

A.R. Cameron and F.C. Baldock, "A new probablility formula to substantiate freedom from disease", Prev. Vet. Med. 34 (1998), pp. 1-17.

A.R. Cameron and F.C. Baldock, "Two-stage sampling surveys to substantiate freedom from disease", Prev. Vet. Med. 34 (1998), pp. 19-30.

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.

See `LtdSampling`

and `SurveyData`

for additional details.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
data(sheepData)
sheepData$size <- ifelse(sheepData$nSheep < 30, "small", "large")
riskValueData <- data.frame(riskGroup = c("small", "large"),
riskValues = c(1,2))
mySurvey <- surveyData(nAnimalVec = sheepData$nSheep,
riskGroupVec = sheepData$size,
riskValueData = riskValueData,
populationData = sheepData, designPrevalence = 0.002,
alpha = 0.05, intraHerdPrevalence = 0.13,
diagSensitivity = 0.9, costHerd = 30, costAnimal = 7.1)
## Limited sampling without risk groups:
myLtdSampling <- ltdSampling(survey.Data = mySurvey, sampleSizeLtd = 7)
## Limited sampling with risk groups:
myLtdSamplingRG <- ltdSampling(survey.Data = mySurvey, sampleSizeLtd = 7,
nSampleFixVec = NULL, probVec = c(1,4))
``` |

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