Best Practices in Quantitative Methods for

The role of quantitative methods in testing developmentalhypotheses is widely recognized, yet even very experiencedquantitative researchers often lack the knowledge requiredfor good decision-making on methodology. The end result isa disconnect between research and practice in methods. Thepurpose of this monograph is to fill a gap in the literature byoffering a series of overviews on common data-analyticissues of particular interest to researchers in child development.Our hope is that this monograph will make alreadydeveloped methods accessible to developmentalists so theycan understand and use them in their research. We start atthe beginning with chapters on data management andmeasurement, two neglected topics in methods trainingdespite the fact that every investigation should begin withproper consideration of each. We follow with two importanttopics for developmental research, missing data and growthmodeling. Missing data can plague developmental workbecause participants sometimes miss one or more assessmentpoints. Growth modeling methods offer researchers atrue means to assess change over time as compared withcruder methods like difference scores and residualizedchange scores. Then comes a discussion of mediation andmoderation, two tools that can be used to elucidate developmentalprocesses. Because so much developmentalscience is non-experimental, we include a chapter on selectionbias that compares five modeling strategies. Proper attentionto data management, measurement, missing data, growthmodeling (whenever possible), mediation and moderation,and potential selection bias is guaranteed to result in greaterprecision in inference-making. Even when researchers makegood decisions about methods, it is critical for them to usegood judgment about the practical importance of findings,so we conclude with this important discussion. We view thismonograph as a first step to getting quantitative researchersstarted and we believe this reference will help researchersmake better-informed decisions about methodology.

Roger Bakeman (Ph.D., University of Texas at Austin) is professor of psychology

at Georgia State University, Atlanta, Georgia. He is the author, with

J. M. Gottman, of Observing Interaction: An Introduction to Sequential Analysis

(2nd ed.; 1997), and, with V. Quera, of Analyzing Interaction: Sequential

Analysis With SDIS and GSEQ (1995). His interests include observational

methodology and sequential analysis of observational data.

Denise Brewer (Ph.D., University of North Carolina at Charlotte) is currently

an Assistant Professor at Appalachian State University in the Child

Development Department. She earned her Ph.D. in special education. She

also received her master’s degree from the University of North at Carolina

Chapel Hill in early intervention and family support and her undergraduate

degree from Appalachian State University in birth through kindergarten.

Research interests and background include assessment issues with

young children.

Kristen L. Bub (M.Ed., Harvard Graduate School of Education) is a fifth

year doctoral student in Human Development and Psychology. She earned

her master’s degree in human development, with a concentration in research

methods, from the Harvard Graduate School of Education. Her

research focuses on the role that early education experiences play in children’s

social and academic development.

Margaret Burchinal (Ph.D., University of North Carolina) is a Senior Scientist

and director of the Data Management and Analysis Center at the

Frank Porter Graham Center and Research Professor of Psychology at the

University of North Carolina at Chapel Hill. She is a methodologist who is

best known for her methodological work on longitudinal modeling as well

as for her substantive work on child care.

BEST PRACTICES IN QUANTITATIVE.METHODS FOR DEVELOPMENTALISTS.CONTENTS.EDITORS' PREFACE vii.INTRODUCTION TO THE MONOGRAPH.Kathleen McCartney, Margaret Burchinal, and Kristen L. Bub 1.I. DATA MANAGEMENT: RECOMMENDED PRACTICES.Margaret Burchinal and Eloise Neebe 9.II. MEASUREMENT ISSUES AND PSYCHOMETRICS METHODS.IN DEVELOPMENTAL RESEARCH.Richard G. Lambert, Lauren Nelson, Denise Brewer, and Margaret Burchinal 24.III. MISSING DATA: WHAT TO DO WITH OR WITHOUT THEM.Keith F. Widaman 42.IV. GROWTH CURVE ANALYSIS: AN INTRODUCTION TO VARIOUS.METHODS FOR ANALYZING LONGITUDINAL DATA.Margaret Burchinal, Lauren Nelson, and Michele Poe 65.V. CONTEMPORARY ADVANCES AND CLASSIC ADVICE FOR.ANALYZING MEDIATING AND MODERATING VARIABLES.Eric Dearing and Lawrence C. Hamilton 88.VI. SELECTION, DETECTION, AND REFLECTION.Kathleen McCartney, Kristen L. Bub, and Margaret Burchinal 105.VII. THE PRACTICAL IMPORTANCE OF FINDINGS.Roger Bakeman 127.CONTRIBUTORS 146.STATEMENT OF EDITORIAL POLICY 149

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Best Practices in Quantitative Methods for Developmentalists, Volume 71, Number 3

Summary

Author Biography

Table of Contents

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