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Compute PSU Sampling Design Parameters

Source: R/StoxAnalyticalBaselineFunctions.R
ComputePSUSamplingParameters.Rd

Compute sampling parameters for Primary Sampling Units in multi-stage sampling.

Usage

ComputePSUSamplingParameters(
  StoxBioticData,
  DefinitionMethod = c("AdHocStoxBiotic", "ProportionalPoissonSampling"),
  SamplingUnitId = character(),
  StratificationColumns = character(),
  StratumName = character(),
  Quota = numeric(),
  ExpectedSampleSize = numeric()
)

Arguments

StoxBioticData

StoxBioticData Sample data to construct design parameters from

DefinitionMethod

'AdHocStoxBiotic' or 'ProportionalPoissonSampling'

SamplingUnitId

name of column in 'StoxBioticData' that identifies the Primary Sampling Unit the design is constructed for.

StratificationColumns

name of columns that are to be used to define Strata for sampling. (for DefinitionMethod 'AdHocStoxBiotic'). See PSUSamplingParametersData

StratumName

name of the stratum sampling parameters are calculated for (for DefinitionMethod 'ProportionalPoissonSampling')

Quota

expected total catch in sampling frame in kg (for DefinitionMethod 'ProportionalPoissonSampling')

ExpectedSampleSize

the expected sample size for Possion sampling (for DefinitionMethod 'ProportionalPoissonSampling')

Value

PSUSamplingParametersData

Details

Computes Sampling Design Parameters from data, given some assumptions specified by the 'DefinitionMethod'.

Primary Sampling Units (the argument 'SamplingUnitId') may be identified by any categorical (character, factor) or ordinal (factor, integer) variable in 'StoxBioticData', that are associated with the 'Sample'-table or any table above 'Sample' in the StoxBiotic-hierarchy.

If 'DefinitionMethod' is 'AdHocStoxBiotic', equal probability sampling with fixed sample size will be assumed withing strata, as well as selection with replacement and complete response. This is a reasonable approximation if within-strata sampling is approximately simple random selections, the sample intensitiy is low (only a small fraction of the population is sampled), and non-response is believed to be random. StratificationVariables may be any categorical or ordinal variables in 'StoxBioticData', that are associated with the 'Sample'-table or any table above 'Sample' in the StoxBiotic-hierarchy, and strata will be defined as the combination of these variables. Primary Sampling Units must be selected withing stratum, so the function will fail there are several strata in one PSU.

If 'DefinitionMethod' is 'ProportionalPoissonSampling', Unstratified (singe stratum) Poission sampling with selection probabilities proportional to catch size is assumed. 'SamplingUnitId' must be a variable on the Haul table of 'StoxBioticData' for this option, and the data must contain only one species (SpeciesCategory in 'StoxBioticData'). SelectionProbabilities are assigned based on the total catch of the species in each haul. Specifically, for a haul \(i\); selectionprobabilites, \(p_{i}\) and inclusionprobabilities \(\pi_{i}\) are calculated as:

$$p_{i}=\frac{w_{i}}{W}$$

$$\pi_{i}=1-(1-p_{i})^{n}$$

where:

  • \(w_{i}\) is the sum of all catch weights in haul \(i\) ('CatchFractionWeight' on the 'Sample' table of 'StoxBioticData')

  • \(W\) is the expected total catch in the fishery (argument 'Quota')

  • \(n\) is the expected sample size (argument 'ExpectedSampleSize')

If proportional poisson sampling was actually used to select the sampled records in 'StoxBioticData', sampling parameters would have been obtained prior to sampling, and it is generally preferable to obtain these, and import those via ReadPSUSamplingParameters. Weight-records are sometimes corrected after sampling parameters are calculated, and proper information about non-response can not be recalculated after the fact.

Proportional poisson sampling also allows the sampler to combine rigour and pragmatism, by varying sampling parameters in the course of sample selection. For instance 'n' may be changed during the sampling period, if non-response turns out to be higher than expected. Such flexibilities are not provided by this function, and the approximation may be severely compromised, if such pragmatism is not accounted for.

See also

ReadPSUSamplingParameters, AddPsuStratificationVariables, AssignPSUSamplingParameters, AnalyticalPopulationEstimate

Examples

 # parameters for simple random haul-selection, stratified by GearGroup
 PSUparams <- ComputePSUSamplingParameters(RstoxFDA::StoxBioticDataExample, 
  "AdHocStoxBiotic", 
  "Haul", 
  "GearGroup")
  
 # parameters for haul selection proportional to catch size.
 calculatedPps <- RstoxFDA::ComputePSUSamplingParameters(RstoxFDA::CatchLotteryExample, 
    "ProportionalPoissonSampling", 
    "serialnumber", StratumName = 
    "Nordsjo", Quota = 124*1e6, 
    ExpectedSampleSize = 110)