jdanov: Jdanov's Old-Age Heaping Index

In heaping: Correction of Heaping on Individual Level

Jdanov's Old-Age Heaping Index

Description

Jdanov's index is designed to detect age heaping at very old ages (typically 95+), where data quality is often poorest. It applies the Whipple principle to specific old-age values.

Usage

jdanov(x, Agei = c(95, 100, 105), weight = NULL)

Arguments

x	numeric vector of individual ages.
Agei	numeric vector of specific ages to evaluate (default c(95, 100, 105)).
weight	optional numeric vector of sampling weights.

Details

Calculate Jdanov's index for detecting heaping at very old ages.

The index compares counts at specified old ages to the surrounding 5-year age groups, similar to the standard Whipple approach but focused on the oldest ages where heaping is most problematic.

Interpretation:

• 100: no heaping

• >100: preference for the specified ages

• 500: maximum heaping (all ages at specified values)

Value

A single numeric value representing Jdanov's index.

Author(s)

Matthias Templ

References

Jdanov, D. A., Scholz, R. D., and Shkolnikov, V. M. (2008). Official population statistics and the Human Mortality Database estimates of populations aged 80+ in Germany and nine other European countries. Demographic Research, 19, 1169-1196.

See Also

kannisto for Kannisto's index, coale_li for Coale-Li index.

Other heaping indices: bachi(), coale_li(), heaping_indices(), kannisto(), myers(), noumbissi(), spoorenberg(), whipple()

Examples

# Create old-age data with heaping
set.seed(42)
age <- c(sample(90:110, 2000, replace = TRUE),
         rep(c(95, 100, 105), each = 100))  # Add heaping
jdanov(age)  # Should be > 100

# No heaping
age_uniform <- sample(90:110, 2000, replace = TRUE)
jdanov(age_uniform)  # Should be close to 100

heaping documentation built on Feb. 10, 2026, 1:08 a.m.