دانلود کتاب The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition

A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including:Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approachMethods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatmentsPower analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designsMeasurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.Content: Chapter 1 Review of Basic Statistical Methods (pages 1–24): Chapter 2 Review of Simple Correlated Samples Designs and Associated Analyses (pages 25–33): Chapter 3 ANOVA Basics for One?Factor Randomized Group, Randomized Block, and Repeated Measurement Designs (pages 35–60): Chapter 4 Simple Linear Regression (pages 61–83): Chapter 5 Essentials of Multiple Linear Regression (pages 85–120): Chapter 6 One?Factor Analysis of Covariance (pages 121–157): Chapter 7 Analysis of Covariance through Linear Regression (pages 159–180): Chapter 8 Assumptions and Design Considerations (pages 181–213): Chapter 9 Multiple Comparison Tests and Confidence Intervals (pages 215–228): Chapter 10 Multiple Covariance Analysis (pages 229–246): Chapter 11 Johnson–Neyman and Picked?Points Solutions for Heterogeneous Regression (pages 247–283): Chapter 12 Nonlinear ANCOVA (pages 285–296): Chapter 13 Quasi?ANCOVA: When Treatments Affect Covariates (pages 297–309): Chapter 14 Robust ANCOVA/Robust Picked Points (pages 311–320): Chapter 15 ANCOVA for Dichotomous Dependent Variables (pages 321–332): Chapter 16 Designs with Ordered Treatments and No Covariates (pages 333–354): Chapter 17 ANCOVA for Ordered Treatments Designs (pages 355–364): Chapter 18 Simple Interrupted Time?Series Designs (pages 365–402): Chapter 19 Examples of Single?Case AB Analysis (pages 403–432): Chapter 20 Analysis of Single?Case Reversal Designs (pages 433–452): Chapter 21 Analysis of Multiple?Baseline Designs (pages 453–471): Chapter 22 Power Estimation (pages 473–482): Chapter 23 ANCOVA for Randomized?Block Designs (pages 483–488): Chapter 24 Two?Factor Designs (pages 489–530): Chapter 25 Randomized Pretest–Posttest Designs (pages 531–539): Chapter 26 Multiple Dependent Variables (pages 541–564): Chapter 27 Nonrandomized Studies: Measurement Error Correction (pages 565–573): Chapter 28 Design and Analysis of Observational Studies (pages 575–597): Chapter 29 Common ANCOVA Misconceptions (pages 599–608): Chapter 30 Uncontrolled Clinical Trials (pages 609–617):