Statistical and Methodological Myths and Urban Legends

by Charles E. Lance (Editor), Robert J Vandenberg (Editor)

This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are sustained, in part, upon sound rationale and justification and, in part, upon unfounded lore. Some examples of these "methodological urban legends", as we refer to them in this book, are characterized by manuscript critiques such (a) "your self-report measures suffer from common method bias"; (b) "your item-to-subject ratios are too low"; (c) "you can’t generalize these findings to the real world"; or (d) "your effect sizes are too low". Historically, there is a kernel of truth to most of these legends, but in many cases that truth has been long forgotten, ignored or embellished beyond recognition. This book examines several such legends. Each chapter is organized to (a) what the legend is that "we (almost) all know to be true"; (b) what the "kernel of truth" is to each legend; (c) what the myths are that have developed around this kernel of truth; and (d) what the state of the practice should be. This book meets an important need for the accumulation and integration of these methodological and statistical practices.

432 pages, Paperback

First published October 1, 2008

Reviews

[Takuro Ishikawa · Rating 5 out of 5]

This book will be very difficult to review because it is very technical and contains a lot of great readings; all of them are enlightening. I think I learned more from the following two (the titles are self-explanatory):
- Missing Data Techniques and Low Response Rates.
- Do samples really matter that much?

[Ana · Rating 5 out of 5]

No he leído todo el libro. Pero el capítulo 4 es súper bueno para distinguir las diferencias entre el Análisis factorial y Componentes principales y otras asunciones que suelen hacerse alrededor de estas técnicas.