| |
| |
| Preface | |
| |
| |
| |
| Foundations | |
| |
| |
| |
| Sources of Error | |
| |
| |
| Prescription | |
| |
| |
| Fundamental Concepts | |
| |
| |
| Surveys and Long-Term Studies | |
| |
| |
| Ad-Hoc, Post-Hoc Hypotheses | |
| |
| |
| To Learn More | |
| |
| |
| |
| Hypotheses: The Why of Your Research | |
| |
| |
| Prescription | |
| |
| |
| What Is a Hypothesis? | |
| |
| |
| How Precise Must a Hypothesis Be? | |
| |
| |
| Found Data | |
| |
| |
| Null or Nil Hypothesis | |
| |
| |
| Neyman-Pearson Theory | |
| |
| |
| Deduction and Induction | |
| |
| |
| Losses | |
| |
| |
| Decisions | |
| |
| |
| To Learn More | |
| |
| |
| |
| Collecting Data | |
| |
| |
| Preparation | |
| |
| |
| Response Variables | |
| |
| |
| Determining Sample Size | |
| |
| |
| Fundamental Assumptions | |
| |
| |
| Experimental Design | |
| |
| |
| Four Guidelines | |
| |
| |
| Are Experiments Really Necessary? | |
| |
| |
| To Learn More | |
| |
| |
| |
| Statistical Analysis | |
| |
| |
| |
| Data Quality Assessment | |
| |
| |
| Objectives | |
| |
| |
| Review the Sampling Design | |
| |
| |
| Data Review | |
| |
| |
| To Learn More | |
| |
| |
| |
| Estimation | |
| |
| |
| Prevention | |
| |
| |
| Desirable and Not-So-Desirable Estimators | |
| |
| |
| Interval Estimates | |
| |
| |
| Improved Results | |
| |
| |
| Summary | |
| |
| |
| To Learn More | |
| |
| |
| |
| Testing Hypotheses: Choosing a Test Statistic | |
| |
| |
| First Steps | |
| |
| |
| Test Assumptions | |
| |
| |
| Binomial Trials | |
| |
| |
| Categorical Data | |
| |
| |
| Time-To-Event Data (Survival Analysis) | |
| |
| |
| Comparing the Means of Two Sets of Measurements | |
| |
| |
| Do Not Let Your Software Do Your Thinking For You | |
| |
| |
| Comparing Variances | |
| |
| |
| Comparing the Means of K Samples | |
| |
| |
| Higher-Order Experimental Designs | |
| |
| |
| Inferior Tests | |
| |
| |
| Multiple Tests | |
| |
| |
| Before You Draw Conclusions | |
| |
| |
| Induction | |
| |
| |
| Summary | |
| |
| |
| To Learn More | |
| |
| |
| |
| Strengths and Limitations of Some Miscellaneous Statistical Procedures | |
| |
| |
| Nonrandom Samples | |
| |
| |
| Modem Statistical Methods | |
| |
| |
| Bootstrap | |
| |
| |
| Bayesian Methodology | |
| |
| |
| Meta-Analysis | |
| |
| |
| Permutation Tests | |
| |
| |
| To Learn More | |
| |
| |
| |
| Reporting Your Results | |
| |
| |
| Fundamentals | |
| |
| |
| Descriptive Statistics | |
| |
| |
| Ordinal Data | |
| |
| |
| Tables | |
| |
| |
| Standard Error | |
| |
| |
| p-Values | |
| |
| |
| Confidence Intervals | |
| |
| |
| Recognizing and Reporting Biases | |
| |
| |
| Reporting Power | |
| |
| |
| Drawing Conclusions | |
| |
| |
| Publishing Statistical Theory | |
| |
| |
| A Slippery Slope | |
| |
| |
| Summary | |
| |
| |
| To Learn More | |
| |
| |
| |
| Interpreting Reports | |
| |
| |
| With a Grain of Salt | |
| |
| |
| The Authors | |
| |
| |
| Cost-Benefit Analysis | |
| |
| |
| The Samples | |
| |
| |
| Aggregating Data | |
| |
| |
| Experimental Design | |
| |
| |
| Descriptive Statistics | |
| |
| |
| The Analysis | |
| |
| |
| Correlation and Regression | |
| |
| |
| Graphics | |
| |
| |
| Conclusions | |
| |
| |
| Rates and Percentages | |
| |
| |
| Interpreting Computer Printouts | |
| |
| |
| Summary | |
| |
| |
| To Learn More | |
| |
| |
| |
| Graphics | |
| |
| |
| Is a Graph Really Necessary? | |
| |
| |
| KISS | |
| |
| |
| The Soccer Data | |
| |
| |
| Five Rules for Avoiding Bad Graphics | |
| |
| |
| One Rule for Correct Usage of Three-Dimensional Graphics | |
| |
| |
| The Misunderstood and Maligned Pie Chart | |
| |
| |
| Two Rules for Effective Display of Subgroup Information | |
| |
| |
| Two Rules for Text Elements in Graphics | |
| |
| |
| Multidimensional Displays | |
| |
| |
| Choosing Effective Display Elements | |
| |
| |
| Oral Presentations | |
| |
| |
| Summary | |
| |
| |
| To Learn More | |
| |
| |
| |
| Building a Model | |
| |
| |
| |
| Univariate Regression | |
| |
| |
| Model Selection | |
| |
| |
| Stratification | |
| |
| |
| Further Considerations | |
| |
| |
| Summary | |
| |
| |
| To Learn More | |
| |
| |
| |
| Alternate Methods of Regression | |
| |
| |
| Linear Versus Nonlinear Regression | |
| |
| |
| Least-Absolute-Deviation Regression | |
| |
| |
| Quantile Regression | |
| |
| |
| Survival Analysis | |
| |
| |
| The Ecological Fallacy | |
| |
| |
| Nonsense Regression | |
| |
| |
| Reporting the Results | |
| |
| |
| Summary | |
| |
| |
| To Learn More | |
| |
| |
| |
| Multivariable Regression | |
| |
| |
| Caveats | |
| |
| |
| Dynamic Models | |
| |
| |
| Factor Analysis | |
| |
| |
| Reporting Your Results | |
| |
| |
| A Conjecture | |
| |
| |
| Decision Trees | |
| |
| |
| Building a Successful Model | |
| |
| |
| To Learn More | |
| |
| |
| |
| Modeling Counts and Correlated Data | |
| |
| |
| Counts | |
| |
| |
| Binomial Outcomes | |
| |
| |
| Common Sources of Error | |
| |
| |
| Panel Data | |
| |
| |
| Fixed- and Random-Effects Models | |
| |
| |
| Population-Averaged Generalized Estimating Equation Models (GEEs) | |
| |
| |
| Subject-Specific or Population-Averaged? | |
| |
| |
| Variance Estimation | |
| |
| |
| Quick Reference for Popular Panel Estimators | |
| |
| |
| To Learn More | |
| |
| |
| |
| Validation | |
| |
| |
| Objectives | |
| |
| |
| Methods of Validation | |
| |
| |
| Measures of Predictive Success | |
| |
| |
| To Learn More | |
| |
| |
| Glossary | |
| |
| |
| Bibliography | |
| |
| |
| Author Index | |
| |
| |
| Subject Index | |