198 Madison Avenue, New York, New York 10016 Oxford is a registered trademark of Oxford University Press All rights reserved. Published by Oxford University Press, Inc. Oxford New York Auckland Cape Town Dar es Salaam Hong Kong Karachi Kuala Lumpur Madrid Melbourne Mexico City Nairobi New Delhi Shanghai Taipei Toronto With offices in Argentina Austria Brazil Chile Czech Republic France Greece Guatemala Hungary Italy Japan Poland Portugal Singapore South Korea Switzerland Thailand Turkey Ukraine VietnamĬopyright # 2008 by Oxford University Press, Inc. Series Editor Tony Tripodi, DSW Professor Emeritus, Ohio State Universityĭetermining Sample Size Balancing Power, Precision, and Practicality Patrick Dattaloĭetermining Sample Size Balancing Power,Precision, andPracticalityģ Oxford University Press, Inc., publishes works that further Oxford University’s objective of excellence in research, scholarship, and education. Whether as an introduction to the process for students or as a refresher for experienced researchers, this practical guide is a perfect overview of a crucial but often overlooked step in empirical social work research. He also offers strategies for mitigating pressures to increase sample size when doing so may not be feasible. In concise, example-rich chapters, Dattalo covers sample-size determination using power analysis, confidence intervals, computer-intensive strategies, and ethical or cost considerations, as well as techniques for advanced and emerging statistical strategies such as structural equation modeling, multilevel analysis, repeated measures MANOVA and repeated measures ANOVA.
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This pocket guide shows social work students, educators, and researchers how to prevent some of the mistakes that would result from a wrong sample size decision by describing and critiquing four main approaches to determining sample size.
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Computer programs help, but no single software package exists that allows researchers to determine sample size across all statistical procedures. A researcher's decision about the sample to draw in a study may have an enormous impact on the results, and it rests on numerous statistical and practical considerations that can be difficult to juggle.