Missing data in bioarchaeology II: A test of ordinal and continuous data imputation

ABSTRACT: Abstract

Objectives

Previous research has shown that while missing data are common in bioarchaeological studies, they are seldom handled using statistically rigorous methods. The primary objective of this article is to evaluate the ability of imputation to manage missing data and encourage the use of advanced statistical methods in bioarchaeology and paleopathology. An overview of missing data management in biological anthropology is provided, followed by a test of imputation and deletion methods for handling missing data.

Materials and Methods

Missing data were simulated on complete datasets of ordinal (n = 287) and continuous (n = 369) bioarchaeological data. Missing values were imputed using five imputation methods (mean, predictive mean matching, random forest, expect

SUBMITTER: Wissler A 

PROVIDER: S-EPMC9825894 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature