Full Description
Clinically oriented professionals and students need to understand and evaluate the research and statistics in professional articles, especially given today's emphasis on evidence-based practice. This book demonstrates how the research approach and design help determine the appropriate statistical analysis. Understanding and Evaluating Research in Applied and Clinical Settings features:
*short, independent, chapters that do not have to be read in order;
*a guide to understanding why a particular statistic was selected;
*an emphasis on effects sizes including measures of risk potency;
*numerous cross-disciplinary examples to illustrate the material; and
*methods to help determine practical and clinical significance and their relation to meta-analysis and evidence-based practice.
This book is intended for practitioners and students in psychology, education, counseling, mental and allied health, nursing, and medicine, and as a text for courses on understanding research methods and statistics.
Contents
Contents: Preface. Part I: Introductory Chapters. Framework and Sample Studies. Definition, Purposes, and Dimensions of Research. A Tale of Two Paradigms: Quantitative and Qualitative. Ethical Problems and Principles in Human Research. Ethical Issues Related to Publishing and Reviewing. Part II: Variables and Their Measurement. Research Problems and Variables. Measurement and Descriptive Statistics. Measurement Reliability. Measurement Validity. Data Collection Techniques. Part III: Research Approaches, Questions, and Designs. Quantitative Research Approaches. Research Questions and Hypotheses. Quasi-Experimental Designs. Randomized Experimental Designs. Single-Subject Designs. General Design Classifications. Part IV: Introduction to the Evaluation of Methods and Design. Internal Validity. Sampling and Population External Validity. Evaluating the Validity of a Research Study: An Introduction. Part V: Introduction to Inferential Statistics and Their Interpretation. Introduction to Inferential Statistics and Hypothesis Testing. Problems With Null Hypothesis Significance Testing (NHST). Using Effect Sizes and Confidence Intervals to Interpret the Results of a Statistical Test. Part VI: Selection and Interpretation of Specific Statistics. Selection of Inferential Statistics: An Overview. Single-Factor Between-Groups Designs: Analysis and Interpretation. Single-Factor Repeated-Measures Designs: Analysis and Interpretation. Basic Associational Designs: Analysis and Interpretation. The Chi-Square Test and Accompanying Effect Size Indices. Between Groups Factorial Designs: Analysis and Interpretation. Pretest-Posttest Comparison Group Designs: Analysis and Interpretation. Use and Interpretation of Multiple Regression. Logistic Regression and Discriminant Analysis: Use and Interpretation. Selection and Use of Inferential Statistics: A Summary. Interpretation of Alpha, Factor Analysis, and Principal Components Analysis. Part VII: Application Chapters. Levels of Evidence for Evidence-Based Practice. Meta-Analysis: Formulation and Interpretation. Effect Sizes and Clinical Significance. Part VIII: Evaluation of Research Validity. Framework for a Comprehensive Evaluation of the Research Validity of a Study. Evaluations of Four Sample Articles. Appendices: Research Validity Evaluation Form. Completed Research Validity Evaluation Form. Comparative Numerical Evaluations of the Four Sample Studies. Confusing Terms.
