Research design and statistical modeling in contemplative meditation studies

This chapter discusses latent variable based design and statistical modeling on contemplative measures. We first review the operationalization and dimensionality of the latent construct of mindfulness, followed by a synthesis of the research design and statistical modeling found in recent (2012-2018) empirical studies. After discussions of explicit-macro and implicit-micro explorations in contemplative research, we examine the rhythm decomposition of Electroencephalogram (EEG) in physiological/ contemplative conditions and the differences through statistical modeling. We further discuss the main challenges that need to be addressed in latent variable based research. Finally, after discussing the principal component analysis and common factor analysis of EEG data, we briefly introduce structural equation modeling based time-series analysis for causality inference and intervention effect estimation in contemplative practices.