Best Practices in Quantitative MethodsThe contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features:
Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods. |
Contents
Best Practices in Measurement | |
4 | |
5 | |
13 | |
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Robust | |
Disattenuation ofEffects aBest Practice? Jason W Osborne 17 Computingand Interpreting EffectSizes | |
18 | |
Best Practices in Quantitative Methods | |
20 | |
About the Editor | |
Peter R Killeen 8 Mixed Methods Researchinthe SocialSciences | |
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Common terms and phrases
analysis andthe ANOVA applied approach Assessment associated assumptions Bayesian bootstrap calculate canbe chapter chisquare Cohen computed confidence interval correlation coefficient covariates data set dependent variable Educational effect size effect sizes effects model evaluate example factor Figure function heterogeneity hypothesis imputation independent indicates inference interaction interpretation interrater reliability inthe isthe Journal judges latent likelihood linear logistic regression matching matrix maximum likelihood mean mediation metaanalysis methods missing data missingness moderator multiple multivariate NHST normally distributed null numberof observed odds ratio ofthe onthe outcome outliers parameter estimates Poisson Poisson distribution Poisson regression population practice predicted predictor probability procedures propensity score Psychological quantitative random Rasch measurement Rasch model raters rating scale regression coefficients relationship replication resampling residual Rubin sample specific SPSS squares standard error standardsetting statistical power structural equation modeling Table techniques thatthe tothe treatment values variance