phoneframes | R Documentation |

This dataset contains some variables regarding household expenses for a
sample of 105 households selected from a list of landline phones (frame
A) and a sample of 135 from a list of mobile phones (frame B) in a
particular city in a specific month. These data are taken from the
`Frames2`

package under the GPL-2 or GPL-3 licence.

```
data(phoneframes)
```

- Domain
A factor indicating the domain each household belongs to. In sample A, possible values are "a" if household belongs to domain a or "ab" if household belongs to overlap domain; in sample B, the values are "b" or "ba"

- Feed
Feeding expenses (in euros) at the househould

- Clo
Clothing expenses (in euros) at the household

- Lei
Leisure expenses (in euros) at the household

- Inc
Household income (in euros). Values for this variable are only available for households included in frame A. For households included in domain b, value of this variable is missing

- Tax
Household municipal taxes (in euros) paid. Values for this variable are only available for households included in frame A. For households included in domain b, value of this variable is missing

- M2
Square meters of the house. Values for this variable are only available for households included in frame B. For households included in domain a, value of this variable is missing

- Size
Household size. Values for this variable are only available for households included in frame B. For households included in domain a, value of this variable is missing

- ProbA
First order inclusion probability in frame A. This probability is 0 for households included in domain b.

- ProbB
First order inclusion probability in frame B. This probability is 0 for households included in domain a.

- Stratum
A numeric value indicating the stratum each household belongs to.

The frame A sample, of size `n_A = 105`

, has been drawn from a population of `N_A = 1735`

households with landline phone according to a stratified random sampling. Population units were divided in 6 different strata.
Population sizes of these strata are ```
N_A^h = (727, 375, 113, 186,
115, 219)
```

. `N_{ab} = 601`

of the households composing the
population have, also, mobile phone. On the other hand, frame totals
for auxiliary variables in this frame are `X_{Income}^A = 4300260`

and `X_{Taxes}^A = 215577`

.

The frame B sample, of size `n_B = 135`

, has been drawn from a population of `N_B = 1191`

households with mobile phone according to a simple random sampling without replacement design.
`N_{ab} = 601`

of these households have, also, landline phone. On the other hand, frame totals for auxiliary variables in this frame are `X_{Metres2}^B = 176553`

and `X_{Size}^B = 3529`

`PiklA`

and `PiklB`

are matrices of pairwise sampling
probabilities for the two frames.

`multiframe`

, `reweight`

Original package: https://CRAN.R-project.org/package=Frames2

```
data(phoneframes)
A_in_frames<-cbind(1, DatA$Domain=="ab")
B_in_frames<-cbind(DatB$Domain=="ba",1)
Bdes_pps<-svydesign(id=~1, fpc=~ProbB, data=DatB,pps=ppsmat(PiklB))
Ades_pps <-svydesign(id=~1, fpc=~ProbA,data=DatA,pps=ppsmat(PiklA))
## optimal constant (Hartley) weighting
mf_pps<-multiframe(list(Ades_pps,Bdes_pps),list(A_in_frames,B_in_frames),theta=0.74)
svytotal(~Lei,mf_pps)
Awts<-cbind(1/DatA$ProbA, ifelse(DatA$ProbB==0,0,1/DatA$ProbB))
Bwts<-cbind(ifelse(DatB$ProbA==0,0,1/DatB$ProbA),1/DatB$ProbB )
## dividing by the expected number of selections (BKA or HH estimator)
mf_pps2<-multiframe(list(Ades_pps,Bdes_pps),list(Awts,Bwts),estimator="expected")
svymean(~Lei,mf_pps2)
## Metcalf and Scott approximation
DatB$Stratum<-10
DatB$Frame<-2
DatA$Frame<-1
Dat_both<-rbind(DatA,DatB)
frame_weights<-c(0.742,1-0.742)
Dat_both$fweights<-with(Dat_both, ifelse(Frame==1,
ifelse(Domain=="ab", frame_weights[1]*1/ProbA,1/ProbA),
ifelse(Domain=="ba", frame_weights[2]*1/ProbB, 1/ProbB)))
MSdesign<-svydesign(id=~1, strata=~Stratum, weights=~fweights,data=Dat_both)
svymean(~Lei,MSdesign)
```

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