A Step by Guide to Exploratory Factor Analysis with R and RStudio

Bol Partner

This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using the open source software R. This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using the open source software R. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of R and RStudio code, and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face while applying EFA, along with how to implement, interpret, and report results. Copious scholarly references and quotations are included to support the reader in responding to editorial reviews. This is a valuable resource for upper-level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.

Bol

This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using the open source software R. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of R and RStudio code, and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face while applying EFA, along with how to implement, interpret, and report results. Copious scholarly references and quotations are included to support the reader in responding to editorial reviews. This is a valuable resource for upper-level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.