SHS: Data from the 2001 Survey of Household Spending (SHS),...

In stratification: Univariate Stratification of Survey Populations

Data from the 2001 Survey of Household Spending (SHS), Statistics Canada

Description

This data set contains some variables from the 2001 Survey of Household Spending (SHS) carried out by Statistics Canada. The main purpose of this survey is to obtain detailed information about household spending during the reference year.

Usage

SHS

Format

A data frame with 16057 observations on the following 7 variables.

CASEID

Identification number

WEIGHT

Weight at household level

PROVINCP

Province or territory code

URBRUR

Urban rural code

URBSIZEP

Size of area of residence code

HHINCTOT

Household income before taxes

M101

Household spending on recreation

Details

In this package, HHINCTOT is used as a stratification variable and M101 as a survey variable.

Source

Income Statistics Division, Statistics Canada.

Examples

# Estimation of the response rate
X <- SHS$HHINCTOT[SHS$HHINCTOT>0]
Y <- SHS$M101[SHS$HHINCTOT>0]
Y[Y<0] <- 0
p<-sum(Y>0)/length(Y)

# Study of the relationship between X and Y for the active units
Xactive <- SHS$HHINCTOT[SHS$HHINCTOT>0&SHS$M101>0]
Yactive <- SHS$M101[SHS$HHINCTOT>0&SHS$M101>0]
plot(log(Xactive), log(Yactive))
# Extreme values are omitted for a more robust estimation
keep <- Xactive/Yactive>quantile(Xactive/Yactive,0.01)&
        Xactive/Yactive<quantile(Xactive/Yactive,0.99)    
plot(log(Xactive)[keep], log(Yactive)[keep])
reg <- lm( log(Yactive)[keep]~log(Xactive)[keep] )
summary(reg)

# Stratification assuming X=Y
nomodel <- strata.LH(x=X, CV=0.05, Ls=3, alloc=c(0.5,0,0.5), takeall=0, 
           model="none", algo.control=list(trymany=FALSE, rep=2))
nomodel
var.strata(nomodel, y=Y) # The target CV is far from being reached

# Stratification taking into account a loglinear model with mortality 
# between X and Y, using the estimated parameters values
model <- strata.LH(x=X, CV=0.05, Ls=3, alloc=c(0.5,0,0.5), takeall=0,
         model="loglinear", model.control=list(beta=reg$coef[2],
         sig2=summary(reg)$sigma^2, ph=0.97), initbh=nomodel$bh,
         algo.control=list(trymany=FALSE, rep=2))
model
var.strata(model,y=Y) # The target CV is reached

stratification documentation built on April 7, 2022, 1:13 a.m.