Class "IndSampling"

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Description

Contains the parameters and the data necessary for a survey to substantiate freedom from disease using "individual sampling". Additionally to the survey parameters: design prevalence (=prevalence of the disease under the null hypothesis), overall significance level (=1-confidence), intra-herd prevalence, sensitivity of the diagnostic test, cost per tested animal and cost per tested herd, the object contains the herd sensitivity the number of herds to be tested, the mean overall number of animals to be tested, the expected costs, as well as a lookup table for the number of animals to test depending on the herd size.

Objects from the Class

Objects can be created by calls of the form new("IndSampling", ...).

Slots

surveyData:

Object of class "SurveyData". Contains all the necessary data and specifications for the survey.

herdSensitivity:

Object of class "numeric" with values between 0 and 1. Desired herd sensitivity.

nHerds:

Object of class "numeric". Number of herds to be tested according to the herd sensitivity herdSensitivity.

nHerdsPerRiskGroup:

Object of class "numeric". Number of herds to be tested per risk group (if population is stratified by risk groups).

nSampleFixVec:

Object of class "numeric". Numeric vector containing some NAs (optional argument). For risk groups for which the sample size is fixed it specifies the sample size. For the risk groups for which the sample size was computed it was set to NA (order of the risk groups is the same as in survey.Data@riskValueData).

probVec:

Object of class "numeric". Contains the sample probabilities for those risk groups for which the sample size was computed (=NA entries in nSampleFixVec).

nAnimalsMean:

Object of class "numeric". Expected total number of animals to be tested in the survey.

expectedCost:

Object of class "numeric". Expected costs of the survey.

lookupTable:

Object of class "matrix" with columns N_lower, N_upper and sampleSize containing the number of animals to test for each herd size.

Methods

HTML

signature(x = "IndSampling"): Creates an html file containing the summary data and the diagnostic plots. Title, file name, output directory, css-file, etc. can additionally be specified using the parameters, filename, outdir, CSSFile, Title, as well as all the other parameters of the R2HTML-function HTMLInitFile.

sample

signature(x = "IndSampling", size = c("fixed", "dynamic")): Sample herds using individual sampling. Additionally to the argument x of type IndSampling the method takes an argument size, which is a character string. For size == "fixed" the fixed number of herds given in x@nHerds is sampled using simple random sampling. For size == "dynamic" dynamic sampling is used, i.e., based on real-time computation of the a-posteriori alpha- error the sample is updated until the a-posteriori alpha-error falls below the predefined significance level x@alpha. The return value is a list with two items: indexSample is a vector of indices of the sample corresponding to x@surveyData@nAnimalVec and aPostAlpha containing the a-posteriori alpha-error of the sample.

show

signature(object = "IndSampling"): Display structure of the class and content of the slots.

summary

signature(object = "IndSampling"): Display structure of the class and a summary of the content of the slots.

Note

No notes yet.

Author(s)

Ian Kopacka <ian.kopacka@ages.at>

See Also

The slot surveyData contains an object of the class SurveyData which is created using surveyData. Objects of the class IndSampling are create using the constructor indSampling.

Examples

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## Show the structure of the class:
showClass("IndSampling")
## Create an object:
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)
myIndSampling <- indSampling(survey.Data = mySurvey, herdSensitivity = 0.7)
## Display results:
summary(myIndSampling)
## Write results to an html-file:
## Not run: 
target <- HTMLInitFile(getwd(), filename = "IndSampling")
HTML(myIndSampling)
HTMLEndFile()
## End(Not run)