Description Objects from the Class Slots Methods Note Author(s) See Also Examples
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 can be created by calls of the form new("IndSampling", ...)
.
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.
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
.
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.
signature(object = "IndSampling")
: Display structure of the class and content
of the slots.
signature(object = "IndSampling")
: Display structure of the class and a
summary of the content of the slots.
No notes yet.
Ian Kopacka <ian.kopacka@ages.at>
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
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ## 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)
|
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