nonresponse {survey} | R Documentation

## Experimental: Construct non-response weights

### Description

Functions to simplify the construction of non-reponse weights by combining strata with small numbers or large weights.

### Usage

    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,...)

### Arguments

`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 `"nonresponse"`
`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

### Details

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.

### Value

`nonresponse` and `joinCells` return objects of class `"nonresponse"`, `neighbours` and `sparseCells` return objects of class `"nonresponseSubset"`

### Examples

    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)

[Package survey version 3.19 Index]