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SAGE Quantitative Research Methods

Four Volume Set
Edited by:


January 2011 | 1 760 pages | SAGE Publications Ltd
For more than 40 years, SAGE has been one of the leading international publishers of works on quantitative research methods in the social sciences. This new collection provides readers with a representative sample of the best articles in quantitative methods that have appeared in SAGE journals as chosen by W. Paul Vogt, editor of other successful major reference collections such as Selecting Research Methods (2008) and Data Collection (2010).

The volumes and articles are organized by theme rather than by discipline. Although there are some discipline-specific methods, most often quantitative research methods cut across disciplinary boundaries.

Volume One: Fundamental Issues in Quantitative Research

Volume Two: Measurement for Causal and Statistical Inference

Volume Three: Alternatives to Hypothesis Testing

Volume Four: Complex Designs for a Complex World

 
VOLUME 1: FUNDAMENTAL ISSUES IN QUANTITATIVE RESEARCH
 
General orientations
Ten Statisticians and Their Impacts for Psychologists

Daniel Wright
Conversations about Three Things

Howard Wainer
Minimally Sufficient Research

Christopher Peterson
On Quantitizing

Margarete Sandelowski
 
Experimental Methods
The External Validity of Experiments

Glenn Bracht and Gene Glass
Randomized Trials for the Real World: Making as Few and as Reasonable Assumptions as Possible

Stuart Baker and Barnett Kramer
Having One's Cake and Eating It, Too: Combining true experiments with regression discontinuity designs

Marvin Mandell
 
Survey Research
Capture-Recapture and Anchored Prevalence Estimation of Injecting Drug Users in England: National and regional estimates

Gordon Hay et al
Constructing Summary Indices of Quality of Life: A model for the effect of heterogeneous importance weights

Michael Hagerty and Kenneth Land
Advances in Age-Period-Cohort Analysis

Herbert Smith
Selection Bias in Web Surveys and the Use of Propensity Scores

Matthias Schonlau et al
 
Methods for Missing Data
Estimation of Causal Effects via Principal Stratification When Some Outcomes Are Truncated by "Death"

Junni Zhang and Donald Rubin
Multiple Imputation for Missing Data: A cautionary tale

Paul Allison
Multiple Imputation: Current perspectives

Michael Kenward and James Carpenter
Incomplete Hierarchical Data

Caroline Beunckens et al
 
VOLUME 2: MEASUREMENT FOR CAUSAL AND STATISTICAL INFERENCE
 
Measurement/Coding
The Cost of Dichotomization

Jacob Cohen
Fidelity Criteria: Development, measurement, and validation

Carol Mowbray et al
Controlling Error in Multiple Comparisons, with Examples from State-to-State differences in Educational Achievement

Valerie Williams, Lyle Jones and John Tukey
Surrogate Endpoint Validation: Statistical elegance versus clinical relevance

E.M. Green
 
Causation
Causation in the Social Sciences: Evidence, inference, and purpose

Julian Reiss
Statistical Models for Causation: What inferential leverage do they provide?

David Freedman
Identification of Causal Parameters in Randomized Studies with Mediating Variables

Michael Sobel
Matching Estimators of Causal Effects: Prospects and pitfalls in theory and practice

Stephen Morgan and David Harding
Suppressor Variables in Path Models

Gerard Massen and Arnold Baker
 
Program Evaluation and Individual Assessment
Are Simple Gain Scores Obsolete?

Richard Williams and Donald Zimmerman
Ten Difference Score Myths

Jeffrey Edwards
What Are Value-Added Models Estimating and What Does This Imply for Statistical Practice?

Stephen Raudenbush
Setting Targets for Health Care Performance: Lessons from a case study of the English NHS

Gwyn Bevan
 
Statistical Inference
Correcting a Significance Test for Clustering

Larry Hedges
The Insignificance of Null Hypothesis Significance Testing

Jeff Gill
A Comparison of Statistical Significance Tests for Selecting Equating Functions

Tim Moses
The Choice of Sample Size: A mixed Bayesian/frequentist approach

Hamid Pezeshk et al
 
VOLUME 3: ALTERNATIVES TO HYPOTHESIS TESTING
 
Confidence Intervals and Effect Sizes
Toward Policy-Relevant Benchmarks for Interpreting Effect Sizes: Combining effects with costs

Douglas Harris
Replication and p Intervals: p values predict the future only vaguely, but confidence intervals do much better

Geoff Cumming
Confidence Intervals About Score Reliability Coefficients, Please

Xitao Fan and Bruce Thompson
Finite Sampling Properties of the Point Estimates and Confidence Intervals of the RMSEA

Patrick Curran et al.
 
Meta-analysis
Integrating Findings: The meta-analysis of research

Gene Glass
Reliability Generalization: Exploring variance in measurement error affecting score reliability across studies

Tammi Vacha-Haase
The Relationship Between Sample Sizes and Effect Sizes in Systematic Reviews in Education

Robert Slavin and Dewi Smith
An Exploratory Test for an Excess of Significant Findings

John Ioannidis and Thomas Trikalinos
Expanded Information Retrieval Using Full-Text Searching

Ronald Kostoff
 
Correlation and Regression
Puzzlingly High Correlations in fMRI Studies of Emotion, Personality, and Social Cognition

Edward Vul et al
How Is a Statistical Link Established Between a Human Outcome and a Genetic Variant?

Guang Guo and Daniel Adkins
The Perils of Partialling

Donald Lynam et al
Weighting Regressions by Propensity Scores

David Freedman and Richard Berk
 
Logit and Probit Regression
Comparing Logit and Probit Coefficients across Groups

Paul Allison
An Additional Measure of Overall Effect Size for Logistic Regression Models

Jeff Allen and Huy Le
The Intermediate Endpoint Effect in Logistic and Probit Regression

D.P. Mackinnon et al
An Introduction to Crisp Set QCA with a Comparison to Binary Logistic Regression

Bernard Gofman and Carsten Schneider
 
Categorical Data Analysis
Univariate and Bivariate Loglinear Models for Discrete Test Score Distributions

Paul Holland and Dorothy Thayer
Testing for IIA in the Multinomial Logit Model

Simon Cheng and J. Scott Long
Goodness-of-Fit Tests and Descriptive Measures in Fuzzy-Set Analysis

Scott Eliason and Robin Stryker
Is Optimal Matching Suboptimal?

Matissa Hollister
 
VOLUME 4: COMPLEX DESIGNS FOR A COMPLEX WORLD
 
Structural Equation Modeling
The General Linear Model as Structural Equation Modeling

James Graham
Factor Retention Decisions in Exploratory Factor Analysis: A tutorial on parallel analysis

James Hayton et al
A Comparison of Item Response Theory and Confirmatory Factor Analytic Methodologies for Establishing Measurement Equivalence/Invariance

Adam Meade and Gary Lautenschlarer
The Importance of Structure Coefficients in Structural Equation Modeling Confirmatory Factor Analysis

Bruce Thompson
 
Multilevel Modeling
Multilevel Modeling: A review of methodological issues and applications

Robert Dedrick et al
Estimating Statistical Power and Required Sample Sizes for Organizational Research Using Multilevel Modeling

Charles Scherbaum and Jennifer Ferreter
From Micro to Meso: Critical steps in conceptualizing and conducting multilevel research

Katherine Klein and Steve Kozlowski
Growth Modeling Using Random Coefficient Models: Model building, testing, and illustrations

Paul Bliese and Robert Ployhart
 
Event History, Survival and Longitudinal Analyses
Multi-State Models for Event History Analysis

Per Kragh Andersen and Niels Keiding
Discrete-Time Survival Mixture Analysis

Bengt Muthen and Katherine Masyn
Multilevel Random Coefficient Analyses in Event- and Interval-Contingent Data in Social and Personality Psychology Research

John Nezlek
Business Cycles and Turning Points: A survey of statistical techniques

Michael Massmann et al
 
Computer-Intensive and Hi-Tech Spatial Analysis Methods
The Validity of Publication and Citation Counts for Sociology and Other Select Disciplines

Jake Najman and Belinda Hewitt
A Web Crawler Design for Data Mining

Marc Thelwall
Analysis of Terrorist Social Networks with Fractal Views

Christopher Yang and Marc Sageman
From Schelling to Spatially Explicit Modeling of Urban Ethnic and Economic Residential Dynamics

Itzhak Benenson

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ISBN: 9781848606999
£675.00

SAGE Research Methods is a research methods tool created to help researchers, faculty and students with their research projects. SAGE Research Methods links over 175,000 pages of SAGE’s renowned book, journal and reference content with truly advanced search and discovery tools. Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. Since SAGE Research Methods focuses on methodology rather than disciplines, it can be used across the social sciences, health sciences, and more.

With SAGE Research Methods, researchers can explore their chosen method across the depth and breadth of content, expanding or refining their search as needed; read online, print, or email full-text content; utilize suggested related methods and links to related authors from SAGE Research Methods' robust library and unique features; and even share their own collections of content through Methods Lists. SAGE Research Methods contains content from over 720 books, dictionaries, encyclopedias, and handbooks, the entire “Little Green Book,” and "Little Blue Book” series, two Major Works collating a selection of journal articles, and specially commissioned videos.