A simplified approach to bias estimation for correlations

Abstract

Abstract Objectives We introduce a simple and unified methodology to estimate the bias of Pearson correlation coefficients, partial correlation coefficients, and semi-partial correlation coefficients. Methods Our methodology features non-parametric bootstrapping and can accommodate small sample data without making any distributional assumptions. Results Two examples with R code are provided to illustrate the computation. Conclusions The computation strategy is easy to implement and remains the same, be it Pearson correlation or partial or semi-partial correlation.