DatB: Database of household expenses for frame B
In Frames2: Estimation in Dual Frame Surveys

Description Usage Format Details See Also Examples

This dataset contains some variables regarding household expenses for a sample of 135 households selected from a list of mobile phones (let say, frame B) in a particular city in a specific month.

DatB

Domain: A string indicating the domain each household belongs to. Possible values are "b" if household belongs to domain b or "ba" if household belongs to overlap domain.
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 set to 0.
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 set to 0.
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 set to 0.
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 set to 0.
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.

The 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

PiklB

data(DatB)
attach(DatB)
#Let perform a brief descriptive analysis for the three main variables
param <- data.frame(Feed, Clo, Lei)
summary (param)
hist (Feed)
hist (Clo)
hist (Lei)