Becoming a behavioral science researcher : a guide to producing research that matters / Rex B. Kline

Includes bibliographical references (p. 333-346) and indexes

Promise and problems -- Introduction -- Not ready for prime time -- What students say they need -- Plan of the book -- Career paths for behavioral scientists -- The good, the bad, and the (really) ugly of behavioral science research -- The good -- The bad -- The (really) ugly -- Why? -- Concepts -- The research trinity -- Trinity overview -- Design -- Measurement -- Analysis -- Internal validity -- Construct validity -- Conclusion validity -- External validity and sampling -- Design and analysis -- Chapter overview -- From question to design -- Experimental designs -- Controlled quasi-experimental designs -- Nonequivalent-group designs -- Regression-discontinuity designs -- Other quasi-experimental designs -- Nonexperimental designs -- Resources for learning more -- The truth about statistics -- Study strategy -- A dozen truths about statistics -- What statistical significance really means -- Misinterpretations of statistical significance -- Why are there so many myths? -- Other drawbacks of statistical tests -- In defense of statistical tests -- Recommendations for changing times -- Appendix: Review of statistics fundamentals -- Effect size estimation -- Contexts for estimating effect size -- Families of parametric effect sizes -- Estimating effect size when comparing two samples -- Measures of association for more complex designs -- Effect sizes for dichotomous outcomes -- T-shirt effect sizes, importance, and cautions -- Approximate confidence intervals -- Research examples -- Appendix: Noncentrality interval estimation for effect sizes -- Measurement -- Chapter scope -- The critical yet underappreciated role of measurement -- Measurement process overview -- Resources for finding measures -- Adapting or translating tests -- Evaluation of score reliability and validity -- Checklist for evaluating measures -- Recent developments in test theory -- Skills -- Practical data analysis -- Vision first, then simplicity -- Managing complex analyses (batch to the future) -- Data screening -- Writing -- Plagiarism and academic integrity -- Writing as learning -- Getting started -- The role of style guides -- General principles of good writing -- Principles of good scientific writing -- Writing sections of empirical studies -- Effective graphical displays -- Ready for the big time -- Appendix: Example results section -- Presentations -- Challenges of oral presentations -- Problems with PowerPoint presentations -- Principles for creating effective PowerPoint presentations -- Lessons from multimedia learning -- Other PowerPoint issues -- Poster presentations -- Appendix: example slides, handout, and poster