heaping: Correction of Heaping on Individual Level

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Authors: Matthias Templ
Cited by: 0
References: 1

Abstract

Provides methods for correcting heaping (digit preference) in survey data at the individual record level. Age heaping, where respondents disproportionately report ages ending in 0 or 5, is a common phenomenon that can distort demographic analyses. Unlike traditional smoothing methods that only correct aggregated statistics, this package corrects individual values by replacing a calculated proportion of heaped observations with draws from fitted truncated distributions (log-normal, normal, or uniform). Supports 5-year and 10-year heaping patterns, single heap correction, and optional model-based adjustment to preserve covariate relationships.

Fields of Study & Subjects

Survey Methodology and Nonresponse Survey Sampling and Estimation Techniques Statistical Methods and Bayesian Inference

Publication details

Publication date
9 February 2026
Language
EN
Document type
Dataset