Experimental: Construct non-response weights
Functions to simplify the construction of non-reponse weights by combining strata with small numbers or large weights.
nonresponse(sample.weights, sample.counts, population) sparseCells(object, count=0,totalweight=Inf, nrweight=1.5) neighbours(index,object) joinCells(object,a,...) ## S3 method for class 'nonresponse' weights(object,...)
sample.weights |
table of sampling weight by stratifying variables |
sample.counts |
table of sample counts by stratifying variables |
population |
table of population size by stratifying variables |
object |
object of class |
count |
Cells with fewer sampled units than this are "sparse" |
nrweight |
Cells with higher non-response weight than this are "sparse" |
totalweight |
Cells with average sampling weight times non-response weight higher than this are "sparse" |
index |
Number of a cell whose neighbours are to be found |
a,... |
Cells to join |
When a stratified survey is conducted with imperfect response it is desirable to rescale the sampling weights to reflect the nonresponse. If some strata have small sample size, high non-response, or already had high sampling weights it may be desirable to get less variable non-response weights by averaging non-response across strata. Suitable strata to collapse may be similar on the stratifying variables and/or on the level of non-response.
nonresponse() combines stratified tables of population size,
sample size, and sample weight into an object. sparseCells
identifies cells that may need combining. neighbours describes the
cells adjacent to a specified cell, and joinCells collapses
the specified cells. When the collapsing is complete, use
weights() to extract the nonresponse weights.
nonresponse and joinCells return objects of class "nonresponse",
neighbours and sparseCells return objects of class "nonresponseSubset"
data(api) ## pretend the sampling was stratified on three variables poptable<-xtabs(~sch.wide+comp.imp+stype,data=apipop) sample.count<-xtabs(~sch.wide+comp.imp+stype,data=apiclus1) sample.weight<-xtabs(pw~sch.wide+comp.imp+stype, data=apiclus1) ## create a nonresponse object nr<-nonresponse(sample.weight,sample.count, poptable) ## sparse cells sparseCells(nr) ## Look at neighbours neighbours(3,nr) neighbours(11,nr) ## Collapse some contiguous cells nr1<-joinCells(nr,3,5,7) ## sparse cells now sparseCells(nr1) nr2<-joinCells(nr1,3,11,8) nr2 ## one relatively sparse cell sparseCells(nr2) ## but nothing suitable to join it to neighbours(3,nr2) ## extract the weights weights(nr2)
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