Improving the stability of bivariate correlations using informative Bayesian priors: a Monte Carlo simulation study.

ABSTRACT:

Objective

Much of psychological research has suffered from small sample sizes and low statistical power, resulting in unstable parameter estimates. The Bayesian approach offers a promising solution by incorporating prior knowledge into statistical models, which may lead to improved stability compared to a frequentist approach.

Methods

Simulated data from four populations with known bivariate correlations (ρ = 0.1, 0.2, 0.3, 0.4) was used to estimate the sample correlation as samples were sequentially added from the population, from n = 10 to n = 500. The impact of three different, subjectively defined prior distributions (weakly, moderately, and highly informative) was investigated and compared to a frequentist model.

Results

The results show that bivari

SUBMITTER: Delfin C 

PROVIDER: S-EPMC10517051 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature