Multivariate Bayesian Analyses in Nursing Research: An Introductory Guide.

In the era of precision health, nursing research has increasingly focused on the analysis of large, multidimensional data sets containing multiple correlated phenotypes (e.g., symptoms). This presents challenges for statistical analyses, especially in genetic association studies. For example, the inclusion of multiple symptoms within a single model can raise concerns about multicollinearity, while individual SNP-symptom analyses may obscure complex relationships. As such, many traditional statistical approaches often fall short in providing a comprehensive understanding of the complexity inherent in many nursing-focused research questions. Multivariate Bayesian approaches offer the unique advantage of allowing researchers to ask questions that are not feasible with traditional approaches. Specifically, these methods support the simultaneous exploration of multiple phenotypes, accounting for the underlying correlational structure between variables, and allow for formal incorporation of existing knowledge into the statistical model. By doing so, they may provide a more realistic view of statistical relationships within a