LtdSampling-class {FFD} | R Documentation |
Class "LtdSampling"
Description
Contains the parameters and the data necessary for a survey to substantiate freedom from disease using "limited 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 mean herd sensitivity, the number of herds to be tested, the mean overall number of animals to be tested and the expected costs.
Objects from the Class
Objects can be created by calls of the form new("LtdSampling", ...)
.
Slots
surveyData
:Object of class
"SurveyData"
. Contains all the necessary data and specifications for the survey.sampleSizeLtd
:Object of class
"numeric"
. Pre-fixed number of animals to be tested per holding, irrespective of the herd size. If a herd contains fewer animals the entire herd is tested.meanHerdSensitivity
:Object of class
"numeric"
with values between 0 and 1. Mean herd sensitivity in the population.meanHerdSensPerRG
:Object of class
"numeric"
with values between 0 and 1. Mean herd sensitivity of each risk group (if population is stratified by risk groups).nHerds
:Object of class
"numeric"
. Number of herds to be tested according to the herd sensitivitymeanHerdSensitivity
.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 insurvey.Data@riskValueData
).probVec
:Object of class
"numeric"
. Contains the sample probabilities for those risk groups for which the sample size was computed (=NA entries innSampleFixVec
).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.
Methods
- HTML
signature(x = "LtdSampling")
: 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-functionHTMLInitFile
.- sample
signature(x = "LtdSampling", size = c("fixed", "dynamic"))
: Sample herds using limited sampling. Additionally to the argumentx
of typeLtdSampling
the method takes an argumentsize
, which is a character string. Forsize == "fixed"
the fixed number of herds given inx@nHerds
is sampled using simple random sampling. Forsize == "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 tox@surveyData@nAnimalVec
andaPostAlpha
containing the a-posteriori alpha-error of the sample.- show
signature(object = "LtdSampling")
: Display structure of the class and content of the slots.- summary
signature(object = "LtdSampling")
: 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 LtdSampling
are create using the constructor
ltdSampling
.
Examples
## Show the structure of the class:
showClass("LtdSampling")
## 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)
myLtdSampling <- ltdSampling(survey.Data = mySurvey, sampleSizeLtd = 7)
## Display results:
summary(myLtdSampling)
## Write results to an html-file:
## Not run:
target <- HTMLInitFile(getwd(), filename = "LtdSampling")
HTML(myLtdSampling)
HTMLEndFile()
## End(Not run)