surveyData: Constructor for class 'SurveyData'.
In FFD: Freedom from Disease

Description Usage Arguments Value Author(s) See Also Examples

Constructor for objects of the class 'SurveyData'.

surveyData(nAnimalVec = numeric(), riskGroupVec = character(),
	riskValueData = data.frame(), populationData = data.frame(), 
    designPrevalence = numeric(), alpha = numeric(), 
    intraHerdPrevalence = numeric(), diagSensitivity = numeric(), 
    costHerd = numeric(), costAnimal = numeric())

`nAnimalVec`	Positive numeric vector containing the number of animals per holding.
`riskGroupVec`	Character vector. Vector containing the the name of a risk group to which the farm belongs. Optional argument. If provided, it must have the same length as nAnimalVec.
`riskValueData`	Data frame. Data frame where the first column contains the labels in riskGroupVec and the second column contains the numeric values for the relative infection risk.
`populationData`	Data frame. Columns of the data frame must have the same length as the vector in `nAnimalVec`. The data frame can contain additional data such as herd id, name and address of the owner etc.
`designPrevalence`	Numeric with values between 0 and 1. Prevalence of the disease under the null hypothesis.
`alpha`	Numeric with values between 0 and 1. Type one error for the statistical test (=significance level).
`intraHerdPrevalence`	Numeric with values between 0 and 1. Intra-herd prevalence, i.e., the assumed prevalence of the disease within an infected herd.
`diagSensitivity`	Numeric with values between 0 and 1. Sensitivity of the diagnostic test used.
`costHerd`	Numeric. Cost per tested herd excluding costs for sampling of animals (e.g., travel costs of the vet).
`costAnimal`	Numeric. Cost per tested animal, e.g., drawing of samples + analysis in the lab.

The function returns an object of the class SurveyData.

Ian Kopacka <ian.kopacka@ages.at>

See SurveyData for additional details on the class.

data(sheepData)
mySurvey <- surveyData(nAnimalVec = sheepData$nSheep, 
    populationData = sheepData, designPrevalence = 0.002, 
    alpha = 0.05, intraHerdPrevalence = 0.13,
    diagSensitivity = 0.9, costHerd = 30, costAnimal = 7.1)