Statistical Methods in Neuropsychology [electronic resource] : Common Procedures Made Comprehensible /
Maroof, David Aaron.author.
Statistical Methods in Neuropsychology Common Procedures Made Comprehensible   David Aaron Maroof  Statistics: not only the bane of many a student's existence, but also puzzling to any number of mental health professionals. At the same time, they are necessary in making sound clinical judgments as to clients' cognitive functioning or decline. Without them, a practitioner may be at a loss to explain findings or recommendations, or understand data in context.   The first publication of its kind, Statistical Methods in Neuropsychology brings the broad field of applied statistics and the specialized field of neuropsychology together to simplify and demystify test results. In readable, at times downright funny prose employing the minimum of hard math (and even less hard jargon), this concise volume shows readers how to effectively translate psychometric test data into real-world clinical practice, and offers a fuller understanding of the research literature. The author critiques commonly used statistical methods on the basis of their strengths and weaknesses, and reviews the issues in these key areas:   • Assessing validity. • Statistical assumptions. • Exploratory factor analysis. • Normative data. • Covariates and covariance analysis. • Regression and logistic regression analysis. • Multivariate analysis of variance.   Statistical Methods in Neuropsychology will appeal to a wide variety of neuropsychologists, cognitive neuroscientists, psychiatrists, and experimental psychologists: those who understand statistics but want to know the why behind them, those new to the field and still getting familiar with the formulas, and those wishing to retake the course with a witty, world-class professor.  .
Description based upon print version of record.
""Statistical Methods in Neuropsychology""; ""Preface""; ""Acknowledgments""; ""Contents""; ""Chapter 1: Introduction""; ""Relinquishing the Sturm and Drang of Learning Statistics""; ""Chapter 2: Validity""; ""Introduction""; ""Hypothetical Constructs""; ""But, What Is Validity?""; ""What Are the Types of Validity?""; ""Classify or Predict? Whatâ€?s the Big Deal?""; ""Content Validity""; ""Criterion Validity""; ""Retrospective/Postdictive Validity""; ""Concurrent Validity""; ""Predictive Validity""; ""Construct Validity""; ""Convergent Validity""; ""Divergent Validity""
""Clinical Validation""""Incremental Validity""; ""Ecological Validity""; ""Summary""; ""Chapter 3: Assumptions of Statistical Analyses""; ""Surveying the Damage: Searching for Discrepancies in Data Entry and Ensuring the Appropriate Application of Statistical Analyses""; ""Statistical Assumptions""; ""What Are the Most Common Statistical Assumptions?""; ""Independence of Observations""; ""Normality""; ""Homogeneity of Variance""; ""Homoscedasticity""; ""Studies that Have Used and Reported Assumptions""; ""Summary""; ""Chapter 4: Exploratory Factor Analysis""; ""An Introduction""
""What Exactly Does EFA Do?""""The Organization of Neuropsychological Constructs""; ""Purposes of EFA""; ""What Are Some Assumptions of EFA?""; ""What Are the Steps for EFA?""; ""Choosing the Model""; ""Extracting Factors""; ""Eigenvalue Rule""; ""Scree Plot/Test""; ""Rotating Factors""; ""Orthogonal Rotation""; ""Oblique Rotation""; ""How Do I Name or Interpret the Factors?""; ""The Adventitious Extras of FA""; ""Comparing Factor Scores""; ""Using Factor Scores as a Step in Subsequent Analysis""; ""Common Sense""; ""Simple Example of EFA in Neuropsychology""; ""Summary""
""Chapter 5: Normative Data in Clinical Neuropsychology""""Introduction""; ""General Categories for Normative Data""; ""Using Normative Data in Clinical Neuropsychology""; ""Importance of Choosing the â€œRightâ€? Normative Data""; ""Discrete (Stratified) Norms""; ""Overlapping Cell Norms""; ""Regression-Based Norms""; ""Robust Norms""; ""Summary""; ""Chapter 6: Covariates and Covariance Analyses""; ""Introduction""; ""Purposes of This Chapter""; ""Confounding Variables in Clinical Practice""; ""Confounding Variables in Research""; ""Main Goal of Using Covariates""
""Methodological Control of Confounding Variables""""Methods and Procedures""; ""Tests Administered""; ""Tests to Exclude Participants""; ""Tests to Include and Group Participants""; ""Test Scores Used Directly in Statistical Analyses""; ""Statistical Control of Confounding Variables""; ""Analysis of Covariance""; ""Three Main Reasons for Choosing ANCOVA""; ""Reducing the Error Term""; ""NonExperimental Designs""; ""Follow-Up Analyses""; ""What to Look for in a Covariate: Itâ€?s Not You, Itâ€?s Me""; ""Assumptions of ANCOVA""; ""Homogeneity of Regression Slopes""; ""Example of ANCOVA""
""Follow-Up Analysis of ANCOVA""
Includes bibliographical references and index.
Statistical Methods in Neuropsychology Common Procedures Made Comprehensible   David Aaron Maroof  Statistics: not only the bane of many a student's existence, but also puzzling to any number of mental health professionals. At the same time, they are necessary in making sound clinical judgments as to clients' cognitive functioning or decline. Without them, a practitioner may be at a loss to explain findings or recommendations, or understand data in context.   The first publication of its kind, Statistical Methods in Neuropsychology brings the broad field of applied statistics and the specialized field of neuropsychology together to simplify and demystify test results. In readable, at times downright funny prose employing the minimum of hard math (and even less hard jargon), this concise volume shows readers how to effectively translate psychometric test data into real-world clinical practice, and offers a fuller understanding of the research literature. The author critiques commonly used statistical methods on the basis of their strengths and weaknesses, and reviews the issues in these key areas:   • Assessing validity. • Statistical assumptions. • Exploratory factor analysis. • Normative data. • Covariates and covariance analysis. • Regression and logistic regression analysis. • Multivariate analysis of variance.   Statistical Methods in Neuropsychology will appeal to a wide variety of neuropsychologists, cognitive neuroscientists, psychiatrists, and experimental psychologists: those who understand statistics but want to know the why behind them, those new to the field and still getting familiar with the formulas, and those wishing to retake the course with a witty, world-class professor.  .
Neuropsychology.
Health informatics.
Experiential research.
Neuropsychology.
Health Informatics.
Psychology Research.