heaping: Correction of Heaping on Individual Level
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