Description Usage Arguments Details Value Examples

View source: R/weightconstruction.R

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

1 2 3 4 5 6 | ```
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"`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | ```
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)
``` |

```
Loading required package: grid
Loading required package: Matrix
Loading required package: survival
Attaching package: 'survey'
The following object is masked from 'package:graphics':
dotchart
sparseCells(nr)
Cells: 3 5 7 11
Indices:
sch.wide comp.imp stype
3 "No" "Yes" "E"
5 "No" "No" "H"
7 "No" "Yes" "H"
11 "No" "Yes" "M"
Summary:
NRwt wt n
3 Inf Inf 0
5 3.2 108 3
7 Inf Inf 0
11 Inf Inf 0
`[.nonresponse`(object, nbour.index)
Cells: 4 7 1
Indices:
sch.wide comp.imp stype
4 "Yes" "Yes" "E"
7 "No" "Yes" "H"
1 "No" "No" "E"
Summary:
NRwt wt n
4 0.92 31.1 112
7 Inf Inf 0
1 1.04 35.2 12
`[.nonresponse`(object, nbour.index)
Cells: 12 9 7
Indices:
sch.wide comp.imp stype
12 "Yes" "Yes" "M"
9 "No" "No" "M"
7 "No" "Yes" "H"
Summary:
NRwt wt n
12 1.290 43.6 14
9 0.916 31.0 8
7 Inf Inf 0
sparseCells(nr1)
Cells: 3 11
Indices:
sch.wide comp.imp stype
3 "No" "Yes" "E"
11 "No" "Yes" "M"
Summary:
NRwt wt n
3 3.78 128 3
11 Inf Inf 0
Call: nonresponse(sample.weight, sample.count, poptable)
12 original cells, 8 distinct cells remaining
Joins:
3 5 7
3 5 7 8 11
counts NRweights totalwts
Min. : 3.00 Min. :0.6840 Min. :23.15
1st Qu.: 7.00 1st Qu.:0.8956 1st Qu.:30.31
Median : 11.00 Median :0.9793 Median :33.15
Mean : 22.88 Mean :1.1461 Mean :38.79
3rd Qu.: 15.50 3rd Qu.:1.3142 3rd Qu.:44.48
Max. :112.00 Max. :2.0977 Max. :71.00
sparseCells(nr2)
Cells: 3
Indices:
sch.wide comp.imp stype
3 "No" "Yes" "E"
Summary:
NRwt wt n
3 2.1 71 10
`[.nonresponse`(object, nbour.index)
Cells: 4 1 6 9 12
Indices:
sch.wide comp.imp stype
4 "Yes" "Yes" "E"
1 "No" "No" "E"
6 "Yes" "No" "H"
9 "No" "No" "M"
12 "Yes" "Yes" "M"
Summary:
NRwt wt n
4 0.920 31.1 112
1 1.040 35.2 12
6 0.835 28.2 4
9 0.916 31.0 8
12 1.290 43.6 14
, , stype = E
comp.imp
sch.wide No Yes
No 1.0389893 2.0976751
Yes 0.6839602 0.9195794
, , stype = H
comp.imp
sch.wide No Yes
No 2.0976751 2.097675
Yes 0.8346383 2.097675
, , stype = M
comp.imp
sch.wide No Yes
No 0.9158863 2.097675
Yes 1.3886018 1.289416
```

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