statistical methods for experiments, quasi-experiments, and single-case studies /
نام نخستين پديدآور
Bradley Huitema
وضعیت ویراست
وضعيت ويراست
2nd ed
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
Hoboken, N.J. :
نام ناشر، پخش کننده و غيره
Wiley,
تاریخ نشرو بخش و غیره
c2011
مشخصات ظاهری
نام خاص و کميت اثر
xvi, 661 p. :
ساير جزييات
ill. ;
ابعاد
25 cm
فروست
عنوان فروست
Wiley series in probability and statistics
یادداشتهای مربوط به کتابنامه ، واژه نامه و نمایه های داخل اثر
متن يادداشت
Includes bibliographical references and index
یادداشتهای مربوط به مندرجات
متن يادداشت
Machine generated contents note: pt. I BASIC EXPERIMENTAL DESIGN AND ANALYSIS -- 1.Review of Basic Statistical Methods -- 1.1.Introduction -- 1.2.Elementary Statistical Inference -- 1.3.Elementary Statistical Decision Theory -- 1.4.Effect Size -- 1.5.Measures of Association -- 1.6.A Practical Alternative to Effect Sizes and Measures of Association That Is Relevant to the Individual: p(YTX > Y Control) -- 1.7.Generalization of Results -- 1.8.Control of Nuisance Variation -- 1.9.Software -- 1.10.Summary -- 2.Review of Simple Correlated Samples Designs and Associated Analyses -- 2.1.Introduction -- 2.2.Two-Level Correlated Samples Designs -- 2.3.Software -- 2.4.Summary -- 3.ANOVA Basics for One-Factor Randomized Group, Randomized Block, and Repeated Measurement Designs -- 3.1.Introduction -- 3.2.One-Factor Randomized Group Design and Analysis -- 3.3.One-Factor Randomized Block Design and Analysis -- 3.4.One-Factor Repeated Measurement Design and Analysis -- 3.5.Summary -- pt. II ESSENTIALS OF REGRESSION ANALYSIS -- 4.Simple Linear Regression -- 4.1.Introduction -- 4.2.Comparison of Simple Regression and ANOVA -- 4.3.Regression Estimation, Inference, and Interpretation -- 4.4.Diagnostic Methods: Is the Model Apt? -- 4.5.Summary -- 5.Essentials of Multiple Linear Regression -- 5.1.Introduction -- 5.2.Multiple Regression: Two-Predictor Case -- 5.3.General Multiple Linear Regression: m Predictors -- 5.4.Alternatives to OLS Regression -- 5.5.Summary -- pt. III ESSENTIALS OF SIMPLE AND MULTIPLE ANCOVA -- 6.One-Factor Analysis of Covariance -- 6.1.Introduction -- 6.2.Analysis of Covariance Model -- 6.3.Computation and Rationale -- 6.4.Adjusted Means -- 6.5.ANCOVA Example 1: Training Effects -- 6.6.Testing Homogeneity of Regression Slopes -- 6.7.ANCOVA Example 2: Sexual Activity Reduces Lifespan -- 6.8.Software -- 6.9.Summary -- 7.Analysis of Covariance Through Linear Regression -- 7.1.Introduction -- 7.2.Simple Analysis of Variance Through Linear Regression -- 7.3.Analysis of Covariance Through Linear Regression -- 7.4.Computation of Adjusted Means -- 7.5.Similarity of ANCOVA to Part and Partial Correlation Methods -- 7.6.Homogeneity of Regression Test Through General Linear Regression -- 7.7.Summary -- 8.Assumptions and Design Considerations -- 8.1.Introduction -- 8.2.Statistical Assumptions -- 8.3.Design and Data Issues Related to the Interpretation of ANCOVA -- 8.4.Summary -- 9.Multiple Comparison Tests and Confidence Intervals -- 9.1.Introduction -- 9.2.Overview of Four Multiple Comparison Procedures -- 9.3.Tests on All Pairwise Comparisons: Fisher-Hayter -- 9.4.All Pairwise Simultaneous Confidence Intervals and Tests: Tukey-Kramer -- 9.5.Planned Pairwise and Complex Comparisons: Bonferroni -- 9.6.Any or All Comparisons: Scheffe -- 9.7.Ignore Multiple Comparison Procedures? -- 9.8.Summary -- 10.Multiple Covariance Analysis -- 10.1.Introduction -- 10.2.Multiple ANCOVA Through Multiple Regression -- 10.3.Testing Homogeneity of Regression Planes -- 10.4.Computation of Adjusted Means -- 10.5.Multiple Comparison Procedures for Multiple ANCOVA -- 10.6.Software: Multiple ANCOVA and Associated Tukey-Kramer Multiple Comparison Tests Using Minitab -- 10.7.Summary -- pt. IV ALTERNATIVES FOR ASSUMPTION DEPARTURES -- 11.Johnson-Neyman and Picked-Points Solutions for Heterogeneous Regression -- 11.1.Introduction -- 11.2.J-N and PPA Methods for Two Groups, One Covariate -- 11.3.A Common Method That Should Be Avoided -- 11.4.Assumptions -- 11.5.Two Groups, Multiple Covariates -- 11.6.Multiple Groups, One Covariate -- 11.7.Any Number of Groups, Any Number of Covariates -- 11.8.Two-Factor Designs -- 11.9.Interpretation Problems -- 11.10.Multiple Dependent Variables -- 11.1.J Nonlinear Johnson-Neyman Analysis -- 11.12.Correlated Samples -- 11.13.Robust Methods -- 11.14.Software -- 11.15.Summary -- 12.Nonlinear ANCOVA -- 12.1.Introduction -- 12.2.Dealing with Nonlinearity -- 12.3.Computation and Example of Fitting Polynomial Models -- 12.4.Summary -- 13.Quasi-ANCOVA: When Treatments Affect Covariates -- 13.1.Introduction -- 13.2.Quasi-ANCOVA Model -- 13.3.Computational Example of Quasi-ANCOVA -- 13.4.Multiple Quasi-ANCOVA -- 13.5.Computational Example of Multiple Quasi-ANCOVA -- 13.6.Summary -- 14.Robust ANCOVA/Robust Picked Points -- 14.1.Introduction -- 14.2.Rank ANCOVA -- 14.3.Robust General Linear Model -- 14.4.Summary -- 15.ANCOVA for Dichotomous Dependent Variables -- 15.1.Introduction -- 15.2.Logistic Regression -- 15.3.Logistic Model -- 15.4.Dichotomous ANCOVA Through Logistic Regression -- 15.5.Homogeneity of Within-Group Logistic Regression -- 15.6.Multiple Covariates -- 15.7.Multiple Comparison Tests -- 15.8.Continuous Versus Forced Dichotomy Results -- 15.9.Summary -- 16.Designs with Ordered Treatments and No Covariates -- 16.1.Introduction -- 16.2.Qualitative, Quantitative, and Ordered Treatment Levels -- 16.3.Parametric Monotone Analysis -- 16.4.Nonparametric Monotone Analysis -- 16.5.Reversed Ordinal Logistic Regression -- 16.6.Summary -- 17.ANCOVA for Ordered Treatments Designs -- 17.1.Introduction -- 17.2.Generalization of the Abelson-Tukey Method to Include One Covariate -- 17.3.Abelson-Tukey: Multiple Covariates -- 17.4.Rank-Based ANCOVA Monotone Method -- 17.5.Rank-Based Monotone Method with Multiple Covariates -- 17.6.Reversed Ordinal Logistic Regression with One or More Covariates -- 17.7.Robust R-Estimate ANCOVA Monotone Method -- 17.8.Summary -- pt. V SINGLE-CASE DESIGNS -- 18.Simple Interrupted Time-Series Designs -- 18.1.Introduction -- 18.2.Logic of the Two-Phase Design -- 18.3.Analysis of the Two-Phase (AB) Design -- 18.4.Two Strategies for Time-Series Regression Intervention Analysis -- 18.5.Details of Strategy II -- 18.6.Effect Sizes -- 18.7.Sample Size Recommendations -- 18.8.When the Model Is Too Simple -- 18.9.Summary -- 19.Examples of Single-Case AB Analysis -- 19.1.Introduction -- 19.2.Example I: Cancer Death Rates in the United Kingdom -- 19.3.Example II: Functional Activity -- 19.4.Example III: Cereal Sales -- 19.5.Example IV: Paracetamol Poisoning -- 19.6.Summary -- 20.Analysis of Single-Case Reversal Designs -- 20.1.Introduction -- 20.2.Statistical Analysis of Reversal Designs -- 20.3.Computational Example: Pharmacy Wait Time -- 20.4.Summary -- 21.Analysis of Multiple-Baseline Designs -- 21.1.Introduction -- 21.2.Case I Analysis: Independence of Errors Within and Between Series -- 21.3.Case II Analysis: Autocorrelated Errors Within Series, Independence Between Series -- 21.4.Case III Analysis: Independent Errors Within Series, Cross-Correlation Between Series -- 21.5.Intervention Versus Control Series Design -- 21.6.Summary -- pt. VI ANCOVA EXTENSIONS -- 22.Power Estimation -- 22.1.Introduction -- 22.2.Power Estimation for One-Factor ANOVA -- 22.3.Power Estimation for ANCOVA -- 22.4.Power Estimation for Standardized Effect Sizes -- 22.5.Summary -- 23.ANCOVA for Randomized-Block Designs -- 23.1.Introduction -- 23.2.Conventional Design and Analysis Example -- 23.3.Combined Analysis (ANCOVA and Blocking Factor) -- 23.4.Summary -- 24.Two-Factor Designs -- 24.1.Introduction -- 24.2.ANCOVA Model and Computation for Two-Factor Designs -- 24.3.Multiple Comparison Tests for Adjusted Marginal Means -- 24.4.Two-Factor ANOVA and ANCOVA for Repeated-Measurement Designs -- 24.5.Summary -- 25.Randomized Pretest-Posttest Designs -- 25.1.Introduction -- 25.2.Comparison of Three ANOVA Methods -- 25.3.ANCOVA for Pretest-Posttest Designs -- 25.4.Summary -- 26.Multiple Dependent Variables -- 26.1.Introduction -- 26.2.Uncorrected Univariate ANCOVA -- 26.3.Bonferroni Method -- 26.4.Multivariate Analysis of Covariance (MANCOVA) -- 26.5.MANCOVA Through Multiple Regression Analysis: Two Groups Only -- 26.6.Issues Associated with Bonferroni F and MANCOVA -- 26.7.Alternatives to Bonferroni and MANCOVA -- 26.8.Example Analyses Using Minitab -- 26.9.Summary -- pt.
متن يادداشت
VII QUASI-EXPERIMENTS AND MISCONCEPTIONS -- 27.Nonrandomized Studies: Measurement Error Correction -- 27.1.Introduction -- 27.2.Effects of Measurement Error: Randomized-Group Case -- 27.3.Effects of Measurement Error in Exposure and Covariates: Nonrandomized Design -- 27.4.Measurement Error Correction Ideas -- 27.5.Summary -- 28.Design and Analysis of Observational Studies -- 28.1.Introduction -- 28.2.Design of Nonequivalent Group/Observational Studies -- 28.3.Final (Outcome) Analysis -- 28.4.Propensity Design Advantages -- 28.5.Evaluations of ANCOVA Versus Propensity-Based Approaches -- 28.6.Adequacy of Observational Studies -- 28.7.Summary -- 29.Common ANCOVA Misconceptions -- 29.1.Introduction -- 29.2.SSAT Versus SSINTUITIVE at' Single Covariate Case -- 29.3.SSAT Versus SSINTUITIVE at: Multiple Covariate Case -- 29.4.ANCOVA Versus ANOVA on Residuals -- 29.5.ANCOVA Versus Y/X Ratio -- 29.6.Other Common Misconceptions -- 29.7.Summary -- 30.Uncontrolled Clinical Trials -- 30.1.Introduction -- 30.2.Internal Validity Threats Other Than Regression -- 30.3.Problems with Conventional Analyses -- 30.4.Controlling Regression Effects -- 30.5.Naranjo-Mckean Dual Effects Model -- 30.6.Summary
بدون عنوان
0
بدون عنوان
0
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Analysis of covariance
رده بندی کنگره
شماره رده
QA279
نشانه اثر
.
H83
2011
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )