Table of Contents

Cover

Title page

Copyright page

Preface

Part I: FOUNDATIONS

Chapter 1 Sources of Error

PRESCRIPTION

FUNDAMENTAL CONCEPTS

SURVEYS AND LONG-TERM STUDIES

AD-HOC, POST-HOC HYPOTHESES

TO LEARN MORE

Chapter 2 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

Chapter 3 Collecting Data

PREPARATION

RESPONSE VARIABLES

DETERMINING SAMPLE SIZE

FUNDAMENTAL ASSUMPTIONS

EXPERIMENTAL DESIGN

FOUR GUIDELINES

ARE EXPERIMENTS REALLY NECESSARY?

TO LEARN MORE

Part II: STATISTICAL ANALYSIS

Chapter 4 Data Quality Assessment

OBJECTIVES

REVIEW THE SAMPLING DESIGN

DATA REVIEW

TO LEARN MORE

Chapter 5 Estimation

PREVENTION

DESIRABLE AND NOT-SO-DESIRABLE ESTIMATORS

INTERVAL ESTIMATES

IMPROVED RESULTS

SUMMARY

TO LEARN MORE

Chapter 6 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

Chapter 7 Strengths and Limitations of Some Miscellaneous Statistical Procedures

NONRANDOM SAMPLES

MODERN STATISTICAL METHODS

BOOTSTRAP

BAYESIAN METHODOLOGY

META-ANALYSIS

PERMUTATION TESTS

TO LEARN MORE

Chapter 8 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

Chapter 9 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

Chapter 10 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

Part III: BUILDING A MODEL

Chapter 11 Univariate Regression

MODEL SELECTION

STRATIFICATION

FURTHER CONSIDERATIONS

SUMMARY

TO LEARN MORE

Chapter 12 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

Chapter 13 Multivariable Regression

CAVEATS

DYNAMIC MODELS

FACTOR ANALYSIS

REPORTING YOUR RESULTS

A CONJECTURE

DECISION TREES

BUILDING A SUCCESSFUL MODEL

TO LEARN MORE

Chapter 14 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

Chapter 15 Validation

OBJECTIVES

METHODS OF VALIDATION

MEASURES OF PREDICTIVE SUCCESS

TO LEARN MORE

Glossary

Bibliography

Author Index

Subject Index