More Statistical and Methodological Myths and Urban Legends

In this review of More Statistical and Methodological Myths and Urban Legends, the authors take a clear-eyed approach to persistent but shaky research practices. The book is best for applied researchers, graduate students, and instructors who need a pragmatic, evidence-oriented critique of common methodological claims. Its single biggest reason to buy is the focused explanation of why familiar critiques - from concerns about common method bias to debates over item-to-subject ratios - are often overstated and how to apply sound alternatives in real research.

Key Features

• Topic coverage: Surveys a range of methodological urban legends and explains their historical origins so readers can judge critiques with context.
• Practical guidance: Outlines proper research techniques that help readers replace lore with defensible methods in study design and analysis.
• Concrete critiques: Uses manuscript-style critiques (for example on common method bias and item-to-subject ratios) to show how to evaluate empirical claims.
• Focus on applied statistics: Addresses sample size, missing data bias in correlation matrices, and effect size interpretation to aid everyday research decisions.
• Accessible tone: Written for practitioners and students so complex methodological debates are presented without unnecessary jargon.

Who It's For

This book is ideal for applied statisticians, social science researchers, and graduate students who regularly design studies, analyze data, or review manuscripts and want a clear reference to challenge common but weak critiques. It helps those who need immediate, actionable explanations rather than purely theoretical arguments.

Researchers seeking step-by-step software tutorials or introductory textbook coverage of basic statistics may want a different resource, because this work focuses on critiquing methodological myths and outlining appropriate techniques rather than teaching elementary statistics from scratch.

Pros & Cons

Pros

• Provides clear historical context for common methodological critiques, helping readers separate myth from evidence.
• Offers practical recommendations on sample size and handling missing data that readers can apply to real studies.
• Uses manuscript-style examples to demonstrate how common criticisms are formed and how to respond.

Cons

• Not a stepwise tutorial for statistical software, so novices expecting hands-on code will need supplemental material.

Specifications

Title	More Statistical and Methodological Myths and Urban Legends
Authors	Robert J. Vandenberg, Charles E. Lance
Subject	Statistical and methodological practices in applied research
Topics covered	Sample size, missing data bias in correlation matrices, effect sizes, common method bias
Intended audience	Applied researchers, graduate students, instructors

Our Verdict

More Statistical and Methodological Myths and Urban Legends is a useful, evidence-focused critique for researchers and instructors who want to interrogate common methodological claims and adopt defensible alternatives. Its practical focus and historical perspective make it good value for anyone who reviews manuscripts or designs studies and needs to replace lore with clearer reasoning.

Frequently Asked Questions

Does the book explain how to handle missing data?
Yes, it discusses missing data bias in correlation matrices and provides guidance on how to assess and mitigate related problems.

Will it teach basic statistics or software commands?
No, the book focuses on methodological critique and best practices rather than step-by-step software tutorials or introductory statistical instruction.

Is it suitable for graduate coursework?
Yes, it is well suited as a supplemental text for graduate courses in research methods or applied statistics that examine common methodological claims.