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| Resampling Concepts | |
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| Introduction | |
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| Terms and Notation | |
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| Cases, Attributes, Scores, and Treatments | |
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| Experimental and Observational Studies | |
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| Data Sets, Samples, and Populations | |
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| Parameters, Statistics, and Distributions | |
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| Distribution Functions | |
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| Cases, Attributes, and Distributions | |
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| Attributes, Scores, Groups, and Treatments | |
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| Distributions of Scores and Statistics | |
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| Exercises | |
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| Populations and Random Samples | |
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| Varieties of Populations | |
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| Random Samples | |
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| Random Sampling | |
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| Simple Random Samples | |
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| Exercises | |
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| Statistics and Sampling Distributions | |
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| Statistics and Estimators | |
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| Accuracy of Estimation | |
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| The Sampling Distribution | |
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| Bias of an Estimator | |
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| Standard Error of a Statistic | |
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| RMS Error of an Estimator | |
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| Confidence Interval | |
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| Sampling Distribution Computations | |
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| Exercises | |
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| Testing Population Hypotheses | |
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| Population Statistical Hypotheses | |
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| Population Hypothesis Testing | |
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| Null Sampling Distribution p-Values | |
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| The p-Value of a Directional Test | |
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| The p-Value of a Nondirectional Test | |
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| Exercises | |
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| Parametrics, Pivotals, and Asymptotics | |
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| The Unrealizable Sampling Distribution | |
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| Sampling Distribution of a Sample Mean | |
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| Parametric Population Distributions | |
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| Pivotal Form Statistics | |
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| Asymptotic Sampling Distributions | |
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| Limitations of the Mathematical Approach | |
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| Cls for Normal Population [mu] and [sigma][superscript 2] | |
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| CI for a Normal Population Mean | |
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| CI for a Normal Population Variance | |
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| Nonparametric CI Estimation | |
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| Exercises | |
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| Limitations of Parametric Inference | |
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| Range and Precision of Scores | |
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| Size of Population | |
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| Size of Sample | |
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| Roughness of Population Distributions | |
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| Parameters and Statistics of Interest | |
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| Scarcity of Random Samples | |
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| Resampling Inference | |
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| Resampling Approaches to Inference | |
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| Exercises | |
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| The Real and Bootstrap Worlds | |
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| The Real World of Population Inference | |
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| The Bootstrap World of Population Inference | |
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| Real-World Population Distribution Estimates | |
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| Nonparametric Population Estimates | |
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| Sample Size and Distribution Estimates | |
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| Bootstrap Population Distributions | |
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| Nonparametric Population Estimates | |
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| Exercises | |
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| The Bootstrap Sampling Distribution | |
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| The Bootstrap Conjecture | |
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| Complete Bootstrap Sampling Distributions | |
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| Monte Carlo Bootstrap Distributions | |
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| The Bootstrap Estimate of Standard Error | |
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| The Bootstrap Estimate of Bias | |
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| Simple Bootstrap CI Estimates | |
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| Bootstrap SE, Bias, and CI Estimates | |
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| Example | |
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| Exercises | |
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| Better Bootstrap CIs: The Bootstrap-t | |
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| Pivotal Form Statistics | |
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| The Bootstrap-t Pivotal Transformation | |
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| Forming Bootstrap-t CIs | |
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| Estimating the Standard Error of an Estimate | |
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| Range of Application of the Bootstrap-t | |
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| Iterated Bootstrap CIs | |
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| SEs and CIs for Trimmed Means | |
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| Definition of the Trimmed Mean | |
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| Importance of the Trimmed Mean | |
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| A Note on Outliers | |
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| Determining the Trimming Fraction | |
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| Sampling Distribution of the Trimmed Mean | |
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| Applications | |
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| Exercise | |
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| Better Bootstrap CIs: BCA Intervals | |
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| Bias-Corrected and Accelerated CI Estimates | |
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| Applications of the BCA CI | |
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| Better Confidence Interval Estimates | |
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| Using CI Correction Factors | |
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| Requirements for a BCA CI | |
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| Implementations of the BCA Algorithm | |
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| Exercise | |
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| Bootstrap Hypothesis Testing | |
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| CIs, Null Hypothesis Tests, and p-Values | |
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| Bootstrap-t Hypothesis Testing | |
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| Bootstrap Hypothesis Testing Alternatives | |
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| CI Hypothesis Testing | |
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| Confidence Intervals or p-Values? | |
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| Bootstrap p-Values | |
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| Computing a Bootstrap-t p-Value | |
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| Fixed-[alpha] CIs and Hypotheis Testing | |
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| Computing a BCA CI p-Value | |
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| Exercise | |
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| Randomized Treatment Assignment | |
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| Two Functions of Randomization | |
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| Randomization of Sampled Cases | |
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| Randomization of Available Cases | |
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| Statistical Basis for Local Causal Inference | |
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| Population Hypotheses Revisited | |
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| Monte Carlo Reference Distributions | |
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| Serum Albumen in Diabetic Mice | |
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| Resampling Stats Analysis | |
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| SC Analysis | |
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| S-Plus Analysis | |
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| Exercises | |
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| Strategies for Randomizing Cases | |
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| Independent Randomization of Cases | |
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| Completely Randomized Designs | |
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| Randomized Blocks Designs | |
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| Restricted Randomizations | |
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| Constraints on Rerandomization | |
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| Implementing Case Rerandomization | |
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| Completely Randomized Designs | |
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| Randomized Blocks Designs | |
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| Independent Randomization of Cases | |
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| Restricted Randomization | |
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| Exercises | |
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| Random Treatment Sequences | |
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| Between- and Within-Cases Designs | |
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| Randomizing the Sequence of Treatments | |
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| Causal Inference for Within-Cases Designs | |
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| Sequence Randomization Strategies | |
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| Rerandomizing Treatment Sequences | |
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| Analysis of the AB-BA Design | |
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| Sequences of K ] 2 Treatments | |
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| Exercises | |
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| Between- and Within-Cases Designs | |
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| Between/Within Designs | |
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| Between/Within Resampling Strategies | |
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| Doubly Randomized Available Cases | |
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| Interactions and Simple Effects | |
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| Simple and Main Effects | |
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| Exercise | |
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| Subsamples: Stability of Description | |
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| Nonrandom Studies and Data Sets | |
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| Local Descriptive Inference | |
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| Description Stability and Case Homogeneity | |
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| Subsample Descriptions | |
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| Employing Subsample Descriptions | |
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| Subsamples and Randomized Studies | |
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| Structured and Unstructured Data | |
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| Half-Samples of Unstructured Data Sets | |
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| Subsamples of Source-Structured Cases | |
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| Exercises | |
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| Resampling Applications | |
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| Introduction | |
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| A Single Group of Cases | |
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| Random Sample or Set of Available Cases | |
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| Typical Size of Score Distribution | |
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| Variability of Attribute Scores | |
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| Association Between Two Attributes | |
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| Exercises | |
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| Two Independent Groups of Cases | |
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| Constitution of Independent Groups | |
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| Location Comparisons for Samples | |
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| Magnitude Differences, CR and RB Designs | |
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| Magnitude Differences, Nonrandom Designs | |
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| Study Size | |
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| Exercises | |
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| Multiple Independent Groups | |
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| Multiple Group Parametric Comparisons | |
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| Nonparametric K-Group Comparisons | |
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| Comparisons among Randomized Groups | |
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| Comparisons among Nonrandom Groups | |
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| Adjustment for Multiple Comparisons | |
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| Exercises | |
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| Multiple Factors and Covariates | |
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| Two Treatment Factors | |
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| Treatment and Blocking Factors | |
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| Covariate Adjustment of Treatment Scores | |
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| Exercises | |
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| Within-Cases Treatment Comparisons | |
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| Normal Models, Univariate and Multivariate | |
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| Bootstrap Treatment Comparisons | |
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| Randomized Sequence of Treatments | |
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| Nonrandom Repeated Measures | |
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| Exercises | |
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| Linear Models: Measured Response | |
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| The Parametric Linear Model | |
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| Nonparametric Linear Models | |
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| Prediction Accuracy | |
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| Linear Models for Randomized Cases | |
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| Linear Models for Nonrandom Studies | |
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| Exercises | |
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| Categorical Response Attributes | |
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| Cross-Classification of Cases | |
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| The 2 [times] 2 Table | |
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| Logistic Regression | |
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| Exercises | |
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| Postscript: Generality, Causality, and Stability | |
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| Study Design and Resampling | |
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| Resampling Tools | |
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| References | |
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| Index | |