contrastinf: Generalized linearization of a smooth function of survey...

In convey: Income Concentration Analysis with Complex Survey Samples

Generalized linearization of a smooth function of survey statistics

Description

Generalized linearization of a smooth function of survey statistics

Usage

contrastinf(exprlist, infunlist)

Arguments

exprlist	a call
infunlist	a list of lists, each having two components: value - the estimate value and lin - the linearized variable

Details

The call must use function that deriv knows how to differentiate. It allows to compute the linearized variable of a complex indicator from the linearized variables of simpler component variables, avoiding the formal derivatives calculations.

Value

a list with two components: values - the estimate value and lin - the linearized variable

Author(s)

Djalma Pessoa, Guilherme Jacob, and Anthony Damico

References

Guillaume Osier (2009). Variance estimation for complex indicators of poverty and inequality. Journal of the European Survey Research Association, Vol.3, No.3, pp. 167-195, ISSN 1864-3361, URL https://ojs.ub.uni-konstanz.de/srm/article/view/369.

See Also

svyqsr

Examples

library(survey)
library(laeken)
data(eusilc) ; names( eusilc ) <- tolower( names( eusilc ) )

# linearized design
des_eusilc <- svydesign( ids = ~rb030 , strata = ~db040 ,  weights = ~rb050 , data = eusilc )
des_eusilc <- convey_prep(des_eusilc)

w <- weights(des_eusilc)

# ratio linearization
T1 = list(value = sum(w*eusilc$eqincome) , lin = eusilc$eqincome )
T2 = list(value = sum(w), lin = rep (1, nrow(eusilc)) )
list_all <- list( T1 = T1, T2 = T2)
lin_R = contrastinf (quote(T1/T2), list_all)

# estimate of the variable eqincome mean
lin_R$value
# se estimate of the variable eqincome mean
SE(svytotal(lin_R$lin, des_eusilc))
# to check, use
svymean (~eqincome, des_eusilc)

# quintile share ratio (qsr) linearization
S20 <- svyisq(~ eqincome, design = des_eusilc, .20, linearized = TRUE)
S20_val <- coef (S20); attributes (S20_val) <- NULL
S20_lin <- attr(S20 , "linearized" )
S80 <- svyisq(~ eqincome, design = des_eusilc, .80, linearized = TRUE)
S80_val <- coef (S80); attributes (S80_val) <- NULL
S80_lin <- attr(S80 , "linearized" )
SU <- list (value = S80_val, lin = S80_lin )
SI <- list (value = S20_val, lin = S20_lin )
TOT <- list(value = sum( w * eusilc$eqincome) , lin = eusilc$eqincome )
list_all <- list (TOT = TOT, SI = SI, SU = SU )
lin_QSR <- contrastinf( quote((TOT-SU)/SI), list_all)

# estimate of the qsr
lin_QSR$value
# se estimate of the qsr:
SE(svytotal(lin_QSR$lin, des_eusilc))
# to check, use
svyqsr(~eqincome, des_eusilc )
# proportion of income below the quantile .20
list_all <- list (TOT = TOT, SI = SI )
lin_Lor <- contrastinf( quote(SI/TOT), list_all)
# estimate of the proportion of income below the quantile .20
lin_Lor$value
# se estimate
SE(svytotal(lin_Lor$lin,des_eusilc))

convey documentation built on Oct. 16, 2024, 5:10 p.m.