Vogt SAGE Quantitative Research Methods

1., Four-Volume Set
ISBN: 978-1-4462-7571-9
Verlag: SAGE Publications
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 1760 Seiten, WEB PDF, Format (B × H): 156 mm x 234 mm

Reihe: SAGE Benchmarks in Social Research Methods

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

Autoren/Hrsg.

Vogt, W. (William) Paul

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Forschungsmethodik, Wissenschaftliche Ausstattung
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik

Inhaltsverzeichnis

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 measureme

Über Autor(innen)

Vogt, W. (William) Paul
W. Paul Vogt is Emeritus Professor of Research Methods and Evaluation at Illinois State University where he won both teaching and research awards. He specializes in methodological choice and program evaluation and is particularly interested in ways to integrate multiple methods. His other books include: Tolerance & Education: Learning to Live with Diversity and Difference (Sage Publications, 1998); Quantitative Research Methods for Professionals (Allyn & Bacon, 2007); Education Programs for Improving Intergroup Relations (coedited with Walter Stephan, Teachers College Press, 2004). He is also editor of four 4-volume sets in the series, Sage Benchmarks in Social Research Methods: Selecting Research Methods (2008); Data Collection (2010); Quantitative Research Methods (2011); and, with Burke Johnson, Correlation and Regression Analysis (2012).His most recent publications include the coauthored When to Use What Research Design (2012) and Selecting the Right Analyses for Your Data: Quantitative, Qualitative, and Mixed Methods Approaches (2014).