surveysd (version 2.0.1)

summary.ipf: Generate Summary Output for IPF Calibration

Description

Generates a detailed summary of an Iterative Proportional Fitting (IPF) calibration, providing a complete tool for evaluating the calibration's success and the validity of the resulting weights.

The output is a list of data.tables for a comprehensive evaluation, including:

Calibration Results:

• calib_results_conP_* and calib_results_conH_*: Key diagnostic tables that compare calibrated margins to population targets and assess the goodness of fit via metrics like maxFac.

Data and Diagnostics:

• weighted data: An excerpt of the final dataset with the calculated calibration weights.

• distribution of the weights: A statistical overview of the weight distribution (min, max, CV).

Detailed Margin Comparisons:

• conP_*, conH_*, *_adjusted, *_original, *_rel_diff_*: Tables that compare original sample margins, calibrated margins, and population targets, along with their relative differences.

Usage

# S3 method for ipf
summary(object, ...)

Value

a list of the following outputs

Arguments

object

object of class ipf

...

additional arguments

Examples

if (FALSE) {
# load data
eusilc <- demo.eusilc(n = 1, prettyNames = TRUE)

# personal constraints
conP1 <- xtabs(pWeight ~ age, data = eusilc)
conP2 <- xtabs(pWeight ~ gender + region, data = eusilc)
conP3 <- xtabs(pWeight*eqIncome ~ gender, data = eusilc)

# household constraints
conH1 <- xtabs(pWeight ~ hsize + region, data = eusilc)

# simple usage ------------------------------------------

calibweights1 <- ipf(
 eusilc,
 conP = list(conP1, conP2, eqIncome = conP3),
 bound = NULL,
 verbose = TRUE
)
output <- summary(calibweights1)
# the output can easily be exported to an Excel file, e.g. with
# library(openxlsx)
# write.xlsx(output, "SummaryIPF.xlsx")
}