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More Statistical and Methodological Myths and Urban Legends

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academy
advanced social science statistics
Aggregation Indices
applied
Category=JMA
Category=JMBT
Category=JMJ
Category=KC
Category=KJMK
Category=KJMV5
Category=PBT
CMV Problem
Common Method Variance
Contour Enhanced Funnel Plots
cross-sectional analysis
Direct Range Restriction
effect
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
equation
Factor Loading Differences
Higher Level Construct
HTHM Correlation
IRT Analysis
journal
management
measurement invariance
Missing Data Bias
missing data techniques
MNAR Missingness
modeling
MTHM Correlation
Multivariate Test Statistics
Non-uniform DIF
Observed Scores
Organizational Justice Climate
organizational research methods
outlier detection methods
psychology
Publication Bias Analyses
Referent Shift Consensus Model
sample size calculation
size
structural
Time Lag Designs
Trait Factor Loadings
Uential Outliers
Unit Level Constructs
Univariate Cutoffs

Product details

  • ISBN 9780415838993
  • Weight: 521g
  • Dimensions: 152 x 229mm
  • Publication Date: 05 Nov 2014
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Description

This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are based partially in sound scientific rationale and partially in unfounded lore. Some examples of these “methodological urban legends” are characterized by manuscript critiques such as: (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.”

What do these critiques mean, and what is their historical basis? More Statistical and Methodological Myths and Urban Legends catalogs several of these quirky practices and outlines proper research techniques. Topics covered include sample size requirements, missing data bias in correlation matrices, negative wording in survey research, and much more.
About

Charles E. Lance is Principal, Organizational Research & Development and Professor Emeritus of Industrial/Organizational Psychology at the University of Georgia, USA.

Robert J. Vandenberg is the Robert O. Arnold Professor of Business in the Department of Management, Terry College of Business at the University of Georgia, USA.